Privacy protection system and method by monitoring SNS posts

Abstract

We provide a system that protects personal privacy by preventing infringement of portrait rights and damage caused by being photographed in photos due to unauthorized posting on social media. Solution: Utilizing multiple biometric identifiers, including the user's facial image, 3D body scan, clothing, voice, and movement analysis, posts on social media are constantly monitored. When a reflection is detected, a notification and deletion request is automatically sent. The system is comprised of a composite module that performs monitoring, detection, notification, request, and billing, and detection accuracy is continuously improved using AI. It has a flexible monitoring system according to billing levels and an automatic linking function with social media operators. [Effects] High-precision detection and a sustainable monitoring model will enable the protection of individuals' portrait and privacy rights, as well as the prevention of digital tattoo formation.

Description

[Technical Field]

[0001] The present invention relates to a privacy protection system using multiple biometric authentication technology, and more particularly to a system and method that monitors image and video content on social media platforms by integrating multiple biometric feature information such as a user's face image, body shape, clothing, and voice, and detects with high accuracy any images that include the user's image and that have been published without the user's permission, and automatically requests their deletion. [Background technology]

[0002] In recent years, with the spread of social networking services (SNS), there has been an increase in cases where personal images and videos are posted without the individual's permission. Such unauthorized posting can violate portrait rights and privacy rights, and has become a problem that affects individuals for a long time, such as digital tattoos.

[0003] Many personal authentication systems using facial recognition technology have been developed and are widely used for building entry control, terminal operation authentication, etc. These systems authenticate individuals by extracting features from a user's facial image and comparing them with pre-registered features. However, existing technologies do not provide a comprehensive privacy protection system that continuously monitors images of specific individuals across a wide range of web platforms and automatically takes action when such images are detected. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent application 2023-058520 Summary of the Invention [Problem to be solved by the invention]

[0005] With conventional technology, it was difficult for individuals to constantly monitor whether their images had been posted on social media without permission, and if they were discovered, they had to take action manually. Furthermore, there was no efficient method for detecting specific individuals from a large number of social media posts, nor a system with a function to automatically request deletion after detection.

[0006] In order to solve the above problems, the present invention aims to provide a comprehensive privacy protection system that automatically monitors posts on SNS platforms using users' biometric information and automatically takes action such as requesting deletion if an unauthorized post is detected. [Means for solving the problem]

[0007] The privacy protection system of the present invention is configured to continuously monitor public posts on multiple social media platforms using multiple biometric identifiers generated from a user's facial image, 3D body scan, clothing pattern, voice data, existing photos, etc., and automatically notify the user and request deletion if a user is detected in the post.

[0008] Specifically, it includes a user information registration unit with multiple biometric authentication functions, a social media monitoring unit, a match detection unit, a notification processing unit, and a deletion request unit, which work together to achieve comprehensive privacy protection. The user information registration unit processes a variety of biometric feature information, such as facial images, 3D body scans, clothing patterns, voice data, and existing photos, in an integrated manner to enable highly accurate individual identification. [Effects of the Invention]

[0009] This invention allows users to prevent their images from being posted on social networking sites without permission, and even if they are posted, it is automatically detected and can be dealt with promptly. Multi-biometric authentication enables highly accurate personal identification based on body shape and clothing, even when the face is hidden or the angle is poor. This prevents the formation of digital tattoos and effectively protects individuals' privacy rights.

[0010] In addition, anonymizing biometric information allows for efficient monitoring while protecting users' personal information. 3D scanning and learning from existing photos also allow for stable long-term protection, adapting to changes in appearance over time. DETAILED DESCRIPTION OF THE INVENTION

[0011] In at least one embodiment, the privacy protection system of the present invention generates a facial feature vector from multiple facial images of a user, encrypts it, and stores it as a biometric identifier. This identifier generation process uses a deep convolutional neural network to extract a 128- to 512-dimensional feature vector, which is then anonymized by hashing. The system can perform processing locally on the user's device or in the cloud. The biometric identifier is periodically updated to improve security. Furthermore, detection accuracy is improved by registering facial images taken from multiple angles and lighting conditions.

[0012] In at least one embodiment, the social media monitoring feature supports major platforms such as YouTube (registered trademark), Instagram, TikTok, X (formerly Twitter), and Facebook, and collects public posts using each platform's API or web scraping technology. Collection frequency can be adjusted based on user settings, supporting a wide range of monitoring, from real-time to daily. The system acquires data in a manner that complies with each platform's terms of use and only performs temporary image analysis to avoid copyright infringement. Additionally, a regional setting can be configured to limit the scope of monitoring to posts within Japan. To protect privacy, the system is designed to exclude private accounts and private messages from monitoring.

[0013] In at least one embodiment, the match detection engine performs face detection processing on each frame of collected images and videos and extracts feature vectors from detected face regions. The similarity between the extracted feature vector and the user's biometric identifier is calculated using cosine similarity or Euclidean distance, and a match is determined if it exceeds a threshold. The determination threshold can be adjusted by the user, and options range from high accuracy to high sensitivity. The system also includes a scoring function that takes into account factors such as face size, position in the image, and clarity, reducing false positives due to coincidental similarities. Machine learning is used to continuously improve detection accuracy.

[0014] In at least one embodiment, the notification feature sends a real-time alert to the user when a match is detected. Notification methods can be selected from email, SMS, push notification, and in-app notification. The notification includes detailed information such as the URL of the detected post, poster information, match score, and estimated face location. After receiving the notification, the user can check whether the image is actually their own, and if it is a false positive, the notification can be fed back to the system as learning data. Notification priorities can also be set based on urgency; a high match is sent immediately, while a low match is sent as a periodic batch notification.

[0015] In at least one embodiment, the automatic deletion request function automatically sends a message to the poster of the detected post. The deletion request is sent using the direct message function, comment function, or report function of each social media platform. Message templates are composed of polite text including legal grounds and can be customized by the user. A setting requiring user approval before sending can be selected, and fully automatic and semi-automatic modes are provided. The system also has a function to record the sending history of deletion requests and the response status, which can be used as material for preparing legal action if necessary. A gradual response is also possible if multiple deletion requests are ignored.

[0016] In at least one embodiment, the privacy protection function includes a configuration in which the user's facial image data is not stored as an original image, but only the feature vector is encrypted and stored. The feature vector is processed using a one-way hash function, making it impossible to restore the original image. In addition, all communications within the system are protected by SSL / TLS encryption to prevent eavesdropping by third parties. The user can select the data storage location, which can be local storage, a private cloud, or a distributed storage system. A periodic data deletion function automatically erases monitoring history that is no longer needed. The system is designed to comply with international privacy laws and regulations.

[0017] In at least one embodiment, the search range setting function is configured to allow users to specify the monitoring target in detail. The region setting allows users to target only posts within Japan, and the language setting allows users to monitor only Japanese posts. The function also has the ability to prioritize monitoring of posts containing specific hashtags, keywords, and location information. Users can also focus on monitoring posts from specific industries or communities based on their occupation or activities. Time zone settings allow users to target only posts from specific time periods. These settings allow for efficient use of system resources by avoiding unnecessary monitoring. The search range can be dynamically adjusted and expanded or contracted depending on the situation.

[0018] In at least one embodiment, the clothing recognition function also learns the characteristics of the clothing worn by the user and combines this with facial recognition to improve detection accuracy. Users can register images of the clothing they often wear, and characteristics such as color, pattern, and brand logo are stored in a database. This information is used for correlation analysis with facial recognition results to improve the accuracy of determining the possibility that the clothing is the same person. Multiple clothing patterns depending on the season and occasion can be registered, and appropriate clothing data is referenced depending on the time of year. To protect privacy, clothing data is also converted into feature vectors and anonymized. The system also has a function to learn changes in clothing and automatically update the database.

[0019] In at least one embodiment, the tiered removal request feature includes a configuration that implements increasingly stronger measures in stages if an initial removal request is ignored. The first stage involves sending a polite removal request message, while the second stage involves making a formal request that clearly states the legal basis. The third stage automatically reports the issue to the operators of each social media platform, and the fourth stage involves providing information to a legal representative designated by the user. The interval between each stage can be set by the user and adjusted depending on the urgency of the situation. All tiered response history is recorded and can be used as evidence in legal proceedings. The feature also automatically tracks responses and response status from the other party and suggests appropriate next steps.

[0020] In at least one embodiment, the price negotiation function includes a configuration that automates the request for deletion as well as the request for appropriate compensation for the use of the image. It references a database of market rates for image rights usage fees and calculates an appropriate amount by taking into account the user's popularity, how the image is used, and the spread of the post. The negotiation message presents a specific amount along with legal grounds and also specifies the payment method. When the other party requests negotiation, it either responds automatically or confirms with the user based on the user's pre-defined settings. It also has a function for managing payment history and outstanding cases, and supports requests to debt collection agencies if necessary. It employs price calculation and negotiation procedures that comply with international image rights laws.

[0021] In at least one embodiment, the partial masking feature is configured to obscure specific problematic parts of a deletion request. Rather than requesting the deletion of the entire face, the feature suggests blurring, embedding, or pixelating specific facial features, reducing friction with the poster. Multiple masking options are available, and specific steps for image editing are also provided. The feature also automatically suggests an appropriate masking level based on the user's social status and occupation. The feature also generates a sample image of what the masking process would look like if accepted, providing the poster with a concrete image and encouraging a cooperative response. The masking history is recorded and can be used as reference information for similar cases.

[0022] In at least one embodiment, the real-time notification system includes a configuration that constantly monitors new posts and detects and notifies users within minutes of their images being posted. A high-speed image processing engine and parallel processing technology efficiently identify targets from large volumes of posted data. The urgency of the notification is automatically determined based on the match score and the likelihood of the post spreading, and an alert is sent immediately in the case of a high risk. Notifications are also sent at appropriate times, taking into account the user's current location and time of day. It is also possible to configure the system to avoid notifications during inappropriate times, such as at night or during meetings. The scope of real-time monitoring is dynamically adjusted, and the system has the ability to change priority monitoring areas depending on the user's activity status.

[0023] In at least one embodiment, the learning-enabled detection system is configured to continuously improve detection accuracy based on user feedback. The results of correct / incorrect judgments are reflected in the machine learning algorithm to build a detection model optimized for each individual user. It automatically adapts to facial changes over time and changes in hairstyle and makeup. It also learns patterns of appearance change depending on the season and situation, enabling more accurate judgment. To protect user privacy, the learning data is processed only at the feature vector level, and the original images are not stored. It also includes a mechanism for using ensemble learning to improve detection technology using anonymized data from other users.

[0024] In at least one embodiment, the multilingual support function includes a configuration for monitoring and responding to posts in languages ​​other than Japanese. It supports major languages ​​such as English, Chinese, and Korean, and generates appropriate removal request messages in each language. It provides polite language and legal grounds in each language that take cultural background into consideration, promoting international understanding. The translation function utilizes the latest AI technology to achieve high-quality translations that properly convey nuances. It also generates request content based on applicable laws, taking into account differences in each country's portrait rights laws and personal information protection laws. Support history in multiple languages ​​is also managed, and can be used as reference material for international legal proceedings.

[0025] In at least one embodiment, the corporate functionality is configured to enable talent agencies and companies to protect the privacy of their affiliated talent and employees. The bulk registration and management function for multiple people allows for the efficient creation of a large-scale monitoring system. The scope of monitoring and response level can be individually adjusted by setting each individual's permissions. The administrator dashboard allows for a centralized understanding of the overall monitoring and response status. Response templates can also be set according to the company's public relations policy, allowing for deletion requests that take into consideration the brand image. A collaboration function with the legal department allows for the creation of a workflow that seeks expert judgment in important cases. A detailed report function for each user allows for the analysis of individual exposure status and response performance.

[0026] In at least one embodiment, the preventive monitoring function includes a configuration in which users pre-register when attending a specific event or location to strengthen monitoring during that period. By pre-registering participation information for concerts, sporting events, public gatherings, etc., SNS posts during that period are monitored intensively. By combining location information and time information, highly relevant posts can be efficiently identified. In addition, by collaborating with event organizers, the function also includes a function to warn users about photography within the venue and assist in obtaining prior consent from participants. Preventive measures are also expected to be effective in preventing unauthorized photography itself. Monitoring continues for a certain period after the event ends, ensuring that delayed posts are addressed.

[0027] In at least one embodiment, the legal support function is configured to assist with legal proceedings when a removal request is denied. Professional legal advice is provided through collaboration with affiliated law firms. The evidence preservation function automatically saves screenshots of the problematic post, URLs, poster information, response history, etc. in a format suitable for legal proceedings. It also provides templates for various petitions and certified mail to assist users in self-processing. It also has a function to estimate legal costs and track the progress of legal proceedings. In international cases, it also coordinates collaboration with legal experts in the relevant countries. The results of legal proceedings are accumulated as reference information for future similar cases.

[0028] In at least one embodiment, the sentiment analysis function includes a configuration that analyzes the context and emotional aspects of a post and determines the priority of the response. The text, comments, reactions, etc. accompanying the post are analyzed using natural language processing technology to evaluate whether the post is malicious and the risk of it spreading. Posts with positive contexts are distinguished from posts with negative contexts, and the response method is adjusted. A comprehensive risk assessment is also performed, taking into account the poster's past behavioral patterns, number of followers, influence, etc. An emergency response is automatically selected for posts determined to be high risk, and a mild response is automatically selected for posts determined to be low risk. The results of the sentiment analysis are reported to the user and used to determine the response policy.

[0029] In at least one embodiment, the blockchain proof function is configured to record detection and response history in an unalterable format. Distributed ledger technology securely stores monitoring logs, deletion request history, and responses from the other party. These records can be used as reliable evidence in legal proceedings, and chronological tampering is impossible. It also reliably proves that deletion was carried out or that requests were ignored. To protect privacy, personally identifiable information is encrypted, and only hash values ​​are recorded on the blockchain. This proof system enables reliable submission of evidence, even in international legal proceedings. The smart contract function also enables automatic response under certain conditions.

[0030] In at least one embodiment, the AI ​​teaching function includes a configuration that predicts changes in a user's appearance and aims to improve future detection accuracy. Age-related facial changes, weight gain or loss, changes in hairstyle, etc. are predicted using machine learning, and the detection model is adjusted in advance. Future appearance is estimated from past change patterns, and a feature vector is generated based on this. Changes in clothing and makeup due to changing fashions are also included in the predictions. This prediction function prevents a decline in detection accuracy due to changes in appearance. Prediction accuracy is continuously improved by comparing with actual changes. Users can check the predicted changes in appearance and make corrections as necessary. This is an important function for providing a stable monitoring service over the long term.

[0031] In at least one embodiment, the voice recognition function is configured to monitor the user's voice in video posts. The user's voiceprint data is registered and a matching voice is detected from the audio track of the posted video. The user's presence can be identified by voice, even if the user's face is not visible. The latest deep learning technology is used to extract voice features, maintaining high detection accuracy even in the face of noise and degradation of sound quality. The system also learns the user's speaking habits and frequently used words and phrases to make a comprehensive judgment. To protect privacy, voice data is also anonymized through feature vectorization. Voice detection in multiple languages ​​is supported, enabling international monitoring. Combining voice detection and face detection enables more reliable identification of individuals.

[0032] In at least one embodiment, the collaborative filtering function includes a configuration that refers to the monitoring results of other users with similar characteristics. Detection patterns among groups of users with similar attributes, such as age, gender, and occupation, are analyzed and used to improve the monitoring accuracy of individuals. In addition, the detection results of other users who participated in the same event are referenced to increase the probability of discovering related posts. To protect privacy, the information of other users is referenced in a completely anonymized state. Collaborative learning improves the detection performance of the entire system, allowing even new users to achieve high detection accuracy from the beginning. The anomaly detection function also makes it possible to quickly discover posts with unusual patterns. Users can choose whether to use collaborative filtering, and can also choose completely independent monitoring.

[0033] In at least one embodiment, the counterfeit detection function is configured to detect and prevent abuse with counterfeit images generated using AI technology. It identifies counterfeit content that uses users' faces using deepfake technology and other techniques, enabling faster response. It uses machine learning to learn characteristic artifacts and unnatural aspects of counterfeit images, enabling highly accurate counterfeit detection. It also automatically selects stronger deletion requests and legal action than usual for posts that are likely to be counterfeit. The detection algorithm is also continuously updated to keep up with advances in counterfeiting technology. Users are provided with information on the possibility of counterfeiting, as well as possible methods of abuse and countermeasures. Collaboration with international counterfeiting crime prevention organizations makes it possible to respond to organized abuse.

[0034] In at least one embodiment, the parent-child collaboration function includes a configuration that allows parents to manage the privacy protection of minors. It provides a function that allows parents to register images of their children and monitor and respond on their behalf. It automatically sets an appropriate response level based on the child's age and requests deletion, including educational considerations. It also specifically detects posts related to bullying and harassment and supports collaboration with schools and educational institutions. It automatically tracks changes in a child's appearance as they grow, ensuring continuous protection. Parents are provided with regular monitoring reports, allowing them to confirm the safety of their child's digital environment. It also has a handover function when a child reaches adulthood, allowing for a smooth transition of management. It also includes a function that appropriately represents the rights of minors in legal proceedings.

[0035] In at least one embodiment, the medical collaboration function has a configuration specialized for protecting the privacy of medical professionals and patients. It specially monitors unauthorized filming at medical institutions such as hospitals and clinics and responds with consideration for medical ethics. It prevents unauthorized disclosure of patient medical information and footage of medical professionals working on the job. It references specialized provisions in the Medical Care Act and the Personal Information Protection Act to make deletion requests based on stronger legal grounds. It also has a collaboration function with public relations and legal personnel at medical institutions. In the event of a highly urgent medical information leak, it automatically and immediately notifies the relevant institutions. It provides a comprehensive solution that balances ensuring the safety of medical professionals and protecting patient privacy.

[0036] In at least one embodiment, the educational institution collaboration function includes a configuration that supports the protection of privacy for students and faculty at schools, universities, etc. It monitors unauthorized recording of school events, classroom scenes, club activities, etc., and responds with considerations specific to educational settings. It adopts a phased approach to balance the protection of minors and the smooth implementation of educational activities. It also has an information sharing function between parents, teachers, and school administrators, establishing an appropriate collaboration system. It is also possible to handle posts that are evidence of bullying or harassment in a special manner. It automatically selects responses that comply with guidelines from the Board of Education and the Ministry of Education, Culture, Sports, Science and Technology, enhancing its practicality in educational settings. It includes a function that balances the protection of long-term educational records with individual privacy rights.

[0037] In at least one embodiment, the special disaster function is configured to take into consideration privacy protection during disasters and emergencies. It prevents unauthorized posting of rescue activities and evacuation situations at disaster sites, protecting the dignity of disaster victims. It balances the importance of information sharing during disasters with individuals' right to privacy, and makes exceptions for posts that are of high public interest. It also has a function to temporarily relax monitoring of posts that are useful in searching for missing persons, with the consent of the family. It supports appropriate information management in cooperation with disaster response headquarters and related organizations. As recovery efforts progress, a return to normal monitoring systems is implemented in stages. It realizes a humanitarian response, including consideration for the psychological state unique to disasters.

[0038] In at least one embodiment, the celebrity special feature includes an advanced configuration specifically designed to protect the portrait rights of public figures and celebrities. It responds to the special circumstances of celebrities, who are photographed without permission more frequently than the general public, and provides faster and more effective monitoring. It learns specific patterns of paparazzi and malicious posters and implements preventative measures. It also considers the balance between freedom of the press and portrait rights and provides special treatment for posts from news organizations. It also has a function to automatically adjust the response level based on the celebrity's social status and influence. It distinguishes between well-intentioned posts by fans and malicious posts and selects the appropriate response method. For international celebrities, it is also possible to respond taking into account the laws and cultural backgrounds of each country.

[0039] In at least one embodiment, the elderly support function is designed to be easily usable even by seniors unfamiliar with digital technology. A simplified user interface and voice guidance function eliminate the need for complex setup procedures. It also provides a proxy setup and management function for family members, ensuring privacy protection across generations. It also creates a special vigilance system to address fraud and abuse cases specific to seniors. It supports the protection of a dignified retirement life, including consideration of posts related to medical care and nursing care. It also has a function to automatically contact family members in emergencies and a function to link with relevant organizations. Aftercare, such as telephone support on operation and on-site setup services, is also provided, creating a system that anyone can use with confidence.

[0040] In at least one embodiment, the international response function has a comprehensive configuration that includes monitoring on global social media platforms and support for each country's legal system. It automatically determines differences in personal information protection and portrait rights laws in the United States, Europe, and Asia, and takes action based on the applicable law. It meets the needs of multinational corporations and individuals operating internationally and provides 24-hour monitoring that takes time zones into account. It generates deletion request messages that take into account each country's cultural background and social norms, promoting international understanding and cooperation. It also supports international legal procedures and coordinates cooperation with legal experts in the relevant countries. It also has a damage claim function that accounts for exchange rates and integration with international remittance systems. It aims to establish a new standard for privacy protection in a globalized society.

[0041] In at least one embodiment, the SNS management integration function is configured to execute an API integration agreement with the operator of each SNS platform and automatically process detected images in real time. By directly linking with the operator's content management system, the function notifies the poster and automatically blurs, pixelates, or completely deletes the relevant portion of the image. The processing level is automatically selected based on the user's settings and legal requirements, and supports a range of processing levels from masking only the face to deleting the entire image. It also links with the SNS's machine learning system to enable pre-detection of similar images and preventative upload restrictions. Agreements with operators also enable sharing of processing history and enhanced monitoring of malicious poster accounts. This integration shifts from the traditional reactive approach to proactive prevention, achieving more effective privacy protection.

[0042] In at least one embodiment, the multi-biometric authentication enrollment function has a comprehensive configuration for acquiring and analyzing user characteristics from multiple angles. In addition to facial recognition, it integrates full-body 3D scanning to extract body shape, posture, and walking pattern characteristics; clothing pattern recognition using a high-resolution camera; traditional biometric authentication such as fingerprints, irises, and voiceprints; and automatic feature learning from the user's existing photos. The 3D scan quantifies physical characteristics such as skeletal structure, muscle tone, and height / weight ratio, while the clothing scan extracts visual characteristics such as color, pattern, brand, and material. The photo scanning function automatically selects images of the user from the smartphone's camera roll and social media posting history, learning about changes in appearance over time. This multiple data is weighted by an integrated algorithm, enabling highly accurate identification even in situations where a single authentication factor would be difficult to detect. It also has the ability to dynamically adjust the reliability of each authentication factor and automatically select the optimal detection strategy depending on the environment and conditions.

[0043] In at least one embodiment, the integrated scanning system includes a configuration that combines dedicated and general-purpose devices to provide a flexible registration environment. The dedicated 3D body scanner combines laser measurement technology and photogrammetry to generate a precise 3D model of the entire body, recording detailed information such as skeletal features, joint range of motion, and muscle shape. Clothing recognition uses a multispectral camera to analyze the reflective properties and weave patterns of materials, extracting brand-specific design elements and logo features. A simple scanning function using a smartphone camera utilizes augmented reality technologies such as ARKit and ARCore to achieve highly accurate body measurements even in a home environment. Learning from existing photos automatically generates patterns of appearance change over time through time-series analysis of EXIF ​​information and also provides a function to predict future appearance. Furthermore, biometric information from wearable devices and behavioral pattern data from IoT sensors are integrated to create a multi-layered personal identification system that combines physical and behavioral characteristics.

[0044] In at least one embodiment, the tiered billing system provides a flexible pricing structure based on the user's usage period and functionality level. The basic plan offers a seven-day free monitoring period, followed by tiered billing for continued use. The premium plan allows for 30 days of continuous monitoring, and the enterprise plan allows for 90 days of continuous monitoring, and also offers improved search scope and processing priority. The subscription level determines the frequency of real-time monitoring, retention period, number of accounts that can be monitored simultaneously, the level of automation for deletion requests, and availability of legal support services. Special pricing plans are also offered based on the user's social status and occupation, ranging from the highest level of service for celebrities and politicians to discounted plans for students and seniors. Billing information is recorded in an immutable form using blockchain technology, ensuring transparency of usage history. A tiered service restriction function for non-payment ensures that basic human rights continue to be protected while maintaining an appropriate revenue model.

[0045] In at least one embodiment, the high-precision voice authentication system includes comprehensive voiceprint authentication functionality that analyzes a user's speech characteristics from multiple angles. In addition to basic voiceprint patterns, the system learns speech rate, pitch changes, breathing patterns, pronunciation habits, dialect and accent characteristics, and changes in voice quality due to emotions to build a comprehensive voice recognition model. During enrollment, a variety of speech patterns, from standard text reading, free conversation, singing, and whispering to loud voices, are recorded to improve detection accuracy in all situations. Noisy voice separation technology enables the system to identify a user's voice even when recording in a noisy environment or when multiple people are speaking simultaneously. Machine learning also tracks changes in voice quality due to aging and physical condition, maintaining stable authentication accuracy over the long term. Voice data is converted into feature vectors using frequency analysis and encrypted and stored in a form that makes it impossible to restore the original voice. Real-time voice monitoring detects unauthorized use in live streaming, podcasts, and other situations, and includes functionality for immediate notification and response.

[0046] In at least one embodiment, the detailed video analysis system has an advanced configuration that comprehensively learns a user's dynamic characteristics. Gait pattern analysis quantifies individual movement patterns, such as stride length, cadence, foot landing angle, upper body sway, and arm swing, enabling identification of the individual even from behind or at a distance. Gesture recognition learns hand movements, pointing habits, head movements, and facial expression patterns, allowing identification of individuals from behavioral characteristics even when the user's face is not visible. During video recording, the system asks the user to perform actions based on multiple scenarios, collecting a wide range of data, from everyday behavior to behavior in special situations. Time series analysis learns the sequence of actions from start to finish, allowing overall patterns to be estimated even from partial movements. The system also has adaptive recognition capabilities that take into account movement restrictions due to clothing worn and changes in walking patterns due to weather and road conditions. Only skeletal information is extracted from video data, enabling efficient analysis while protecting privacy.

[0047] In at least one embodiment, the personal photo learning system is equipped with an advanced configuration that automatically extracts and learns features from a user's vast amount of existing image data. It comprehensively analyzes photos from a smartphone's camera roll, various social media accounts, cloud storage, and photos provided by family and friends to construct a time-series pattern of appearance changes. Machine learning automatically distinguishes between the user's photos and those of others, and only images with high confidence are adopted as training data. It simultaneously learns factors that influence appearance changes using metadata such as age, season, location, and event. It also analyzes personal change patterns such as whether or not makeup is worn, hairstyle changes, weight gain or loss, and clothing preferences, and uses these to predict future appearance. It also learns differences in detection accuracy due to image quality and angle, achieving high-accuracy detection even with low-quality images. To protect privacy, the original images are deleted after learning is complete, and only the feature vectors are retained. In mixed images such as family photos, it automatically extracts only the user using facial recognition technology, simultaneously protecting the privacy of those involved.

[0048] In at least one embodiment, the real-time billing management system includes a configuration that provides a dynamic fee adjustment function based on user usage. Basic monitoring only searches posts from the past seven days, with tiered fees applied to searches of posts from earlier than that. A monthly basic fee is charged for searches of the past 30 days, a premium fee for searches of the past year, and a maximum fee for searches of the entire period. The fee level also correlates with the number of monitored social media platforms, the number of simultaneous search threads, the immediacy of result notifications, and the level of automation of deletion requests. Differentiated fees are also offered based on the user's occupation and social status, meeting a wide range of needs, from general users to celebrities. Service is gradually restricted in the event of non-payment, ultimately maintaining only basic human rights protection functions. Billing history is managed on a blockchain to ensure transparency and tamper-proofing. The system also includes a social contribution function that temporarily makes all functions available free of charge in emergencies and disasters. Important cases requiring legal procedures are prioritized regardless of the fee level.

[0049] In at least one embodiment, the comprehensive voice analysis engine has an advanced configuration that analyzes human speech characteristics in multiple dimensions. In addition to basic voiceprints, it learns subtle features such as speech rate patterns, pitch fluctuations, word extensions, pauses between words, and breath depth and timing. It builds a comprehensive voice profile by taking into account dialects, accents, foreign language accents, occupational speech patterns, and age-related differences in speech. It also learns changes in voice quality due to emotional states, tracking the impact of emotions such as anger, sadness, joy, and surprise on the voice. It also distinguishes between temporary changes in voice quality due to colds or poor health and permanent changes due to aging, making appropriate decisions. It also accommodates sound quality degradation due to different recording environments, enabling voice detection in a variety of situations, including outdoors, indoors, in a car, and on a phone call. When multiple people are speaking simultaneously, it uses voice separation technology to extract only the user's voice and analyze it individually. The voice data is digitized using frequency spectrum analysis and stored in a format that cannot be restored to the original audio.

[0050] In at least one embodiment, the technology-agnostic architecture has a flexible configuration that integrates various technology elements in a mutually interchangeable manner. The AI / machine learning engine dynamically selects the optimal algorithm from various algorithms, such as deep learning neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, LSTMs, GANs, decision trees, support vector machines, Bayesian networks, and reinforcement learning, and has the ability to switch between them depending on performance requirements and computational resources. Image sensors can be selected depending on the application, including CCD sensors, CMOS sensors, ToF sensors, LiDAR sensors, infrared sensors, multispectral sensors, hyperspectral sensors, depth sensors, stereo cameras, and 360-degree cameras. Voice input devices support a variety of devices, including condenser microphones, dynamic microphones, directional microphones, omnidirectional microphones, wireless microphones, bone conduction microphones, MEMS microphones, and beamforming microphone arrays.

[0051] In at least one embodiment, the communication technology selection system includes an adaptive configuration that dynamically selects and combines available communication methods. For wireless communication, the system automatically selects the optimal method from 5G, 4G LTE, 3G, WiFi 6, WiFi 6E, WiFi 7, Bluetooth 5.0 or later, NFC, ZigBee, LoRaWAN, satellite communication, quantum communication, etc. For wired communication, the system supports Ethernet, USB-C, Thunderbolt, fiber optics, power line communication, etc. For cloud services, the system supports major providers such as Amazon Web Services, Microsoft Azure, Google Cloud Platform, IBM Cloud, Oracle Cloud, and Alibaba Cloud, as well as various configurations such as private cloud, hybrid cloud, edge computing, and fog computing. For database systems, the system selects from MySQL (registered trademark), PostgreSQL, MongoDB, Redis, Cassandra, Elasticsearch, Neo4j, Apache Kafka, etc. according to requirements, and also utilizes special-purpose databases such as distributed databases, in-memory databases, and time-series databases.

[0052] In at least one embodiment, the display and output technology integrated system is configured to provide a universal interface compatible with a variety of output devices. For visual output, the system supports various display technologies, including LCD, OLED, QLED, E-ink, projectors, holograms, AR displays, VR displays, MR displays, retinal projection displays, and aerial video displays. For resolution, the system supports current and future standards, including HD, Full HD, 4K, 8K, and 16K, and refresh rates ranging from 60Hz to 240Hz, as well as variable refresh rate technologies. For audio output, the system utilizes a variety of audio technologies, including stereo speakers, 5.1-channel, 7.1-channel, Dolby Atmos, DTS:X, binaural audio, bone conduction speakers, directional speakers, and ultrasonic speakers. For haptic feedback, the system provides an intuitive operating experience using technologies such as vibration, force feedback, temperature feedback, electrical stimulation, and ultrasonic haptics.

[0053] In at least one embodiment, the technology advancement adaptability includes advanced configurations that automatically update and expand the system in response to emerging technologies. In artificial intelligence technology, the system supports a gradual transition from currently mainstream deep learning to future technologies such as quantum machine learning, neuromorphic computing, biomimetic AI, and artificial general intelligence (AGI). In sensor technology, the system incorporates support for next-generation technologies, such as quantum dot sensors, graphene sensors, biosensors, and molecular sensors, from current CMOS and CCD sensors. In communications technology, the system supports the evolution from 5G to 6G, terahertz communications, visible light communications, and quantum internet. In computing, the system also considers support for innovative processing devices, such as quantum processors, optical computers, DNA computers, and neuromorphic chips, instead of conventional CPUs and GPUs. The system also automatically adapts to changing technology standards, protocol updates, and evolving security requirements, ensuring continuous system operation.

[0054] In at least one embodiment, the general-purpose platform design enables a highly independent configuration that is not dependent on a specific vendor or product. The operating system is designed to run on a variety of platforms, including Windows, macOS (registered trademark), Linux (registered trademark), Android, iOS, Unix-based operating systems, and real-time operating systems. The programming language is implemented in major languages ​​such as Python, Java, C++, JavaScript, TypeScript, Go, Rust, Swift, and Kotlin, and optimizations are also performed according to the characteristics of each language. The development framework is compatible with current and future frameworks such as TensorFlow, PyTorch, Keras, scikit-learn, OpenCV, React, Vue.js, Angular, Flutter, and React Native. The API design employs standard protocols such as REST, GraphQL, gRPC, and WebSocket, and also utilizes modern design patterns such as microservice architectures, serverless architectures, and container technologies (Docker and Kubernetes). The system also supports both open source and proprietary technologies, providing flexible options that take into account licensing requirements and legal constraints.

[0055] In at least one embodiment, the tiered notification system has a comprehensive configuration that automates detailed progress reports to users from detection to complete removal. The system performs these steps: initial detection immediately notifies the user that a post has been found; when a removal request is sent, a notification confirming the request and its recipient; when a response is received from the poster, a summary of the response; and when the removal is complete, a confirmation of completion and screenshots are saved. User approval at each stage can be configured, ranging from fully automated to incremental confirmation. Notification methods can be configured based on user preference, including email, SMS, push notification, and in-app message. Notification frequency can also be automatically adjusted based on urgency, allowing for immediate notifications for high-risk cases and periodic summary notifications for low-risk cases. Progress history is stored chronologically for future reference or as evidence in legal proceedings.

[0056] In at least one embodiment, the poster response tracking feature includes an advanced configuration that continuously monitors and analyzes the poster's behavioral patterns in response to removal requests. The system tracks the poster's account activity after the request is sent, whether the post has been edited or deleted, whether additional posts have been made, interactions with followers, and similar posts on other platforms 24 / 7. It also learns the poster's behavioral patterns when they ignore the request and automatically suggests countermeasures for future similar cases. If the poster agrees to the removal, the system records their cooperative attitude and prioritizes a more amicable approach in future negotiations with the same poster. The system comprehensively evaluates the poster's speed of response, completeness of the removal, and additional cooperation, and manages this as a trust score. This information is anonymized and used as reference information for other users' cases, contributing to improved negotiation efficiency throughout the system.

[0057] In at least one embodiment, the deletion completion confirmation system is sophisticatedly configured to automate verification of post deletion and reporting to the user. If a deletion request is accepted, the system verifies the complete deletion of the post through multiple methods and tracks its removal from caches and archive sites. Screenshots before and after deletion are automatically captured and saved as evidence of the deletion. Additionally, if the poster partially deletes or edits the post, the system analyzes the detailed changes to determine whether the user's request was properly met. After deletion is complete, the system continues monitoring for a certain period of time to check for reposts or similar posts by the same poster. If complete deletion is confirmed, a deletion completion report is automatically generated for the user, notifying them of the completion of the process. The report includes detailed information such as a comparison of images before and after deletion, the time frame for the process, and an evaluation of the poster's level of cooperation, and is saved for future reference.

[0058] In at least one embodiment, the user reporting function includes a comprehensive configuration that aims to improve transparency and user satisfaction throughout the response process. A detailed response report is automatically generated for each detected post, quantifying detection accuracy, response speed, removal success rate, and poster response. Monthly and yearly comprehensive reports provide comprehensive analysis, including user exposure trends, changes in risk level, analysis of response effectiveness, and improvement suggestions. Additionally, a user feedback function collects false positive reports, satisfaction ratings, and improvement requests, which are used to continuously improve the system. For important cases, legal analysis and additional expert advice are also provided. Reports can be customized to suit the user's level of understanding, from detailed technical versions to simplified versions that only include the key points. A function for regular user interviews is also provided to provide support on how to effectively use the system.

[0059] In at least one embodiment, the evidence preservation system is equipped with a specialized configuration that reliably collects and preserves evidentiary materials required for legal proceedings. For detected posts, detailed information, such as the post content, posting date and time, poster information, distribution status, and number of accesses, is recorded in a legally valid format. Screenshots, URLs, metadata, network information, etc. are saved in a tamper-proof format, and time stamps are also obtained from a timestamp server as needed. The system also records the history of deletion requests, responses from posters, and deletion process, preserving the entire response process in a fully reproducible format. It also includes a function for third-party verification of evidentiary value and can output data in a format suitable for submission to courts or law enforcement agencies. The scope of evidence preservation can be adjusted by the user, ranging from basic records to detailed technical information. The long-term storage function ensures reliable evidence management that complies with legal statutes of limitations.

[0060] In at least one embodiment, the poster profiling function includes an advanced configuration that analyzes the characteristics and tendencies of unauthorized posters and strengthens preventive measures. It comprehensively analyzes the poster's account information, past posting history, follower composition, activity patterns, impact on other users, etc. to assess risk levels. It quickly identifies habitual unauthorized posters and malicious posters and implements stricter monitoring of posts from those accounts. It also analyzes the poster's motives and background, distinguishing between posts made out of simple ignorance and malicious posts, and selecting the appropriate response. It automatically selects an educational approach for well-intentioned posters and a strong response, including legal action, for malicious posters. The profiling results are anonymized and can be used in cases involving other users, contributing to improved response accuracy across the entire system. It also has a function that continuously tracks the poster's improvement and gradually lowers the risk level if the poster demonstrates cooperative behavior.

[0061] In at least one embodiment, the similar post prediction function has an advanced configuration that predicts related posts and future posting risks based on detected posts. It analyzes the possibility of other images or videos taken on the same occasion based on information such as the post's content, location, time, participants, and event. It uses machine learning to learn shooting patterns at specific events or locations and predict posts likely to feature the user in advance. It also analyzes the possibility of additional or related posts based on the poster's past behavioral patterns. It dynamically expands the monitoring range based on the prediction results to detect related posts early. For large-scale events such as seasonal events, sporting events, and concerts, it learns event-specific posting patterns and conducts enhanced monitoring for a limited period of time. Prediction accuracy is continuously improved by comparing with actual detection results and is used to optimize long-term monitoring strategies. Users are also provided with warnings based on the prediction results and advice on behavior during high-risk periods.

[0062] In at least one embodiment, the regional legal response function includes an international configuration that automatically selects the optimal response strategy based on the poster's location and applicable laws. It maintains a database of legal frameworks for portrait rights, personal information protection laws, and privacy rights in each country and region, and automatically determines the applicable law based on the poster's location and language. It selects the most effective removal request strategy, taking into account factors such as the strength of the legal basis, enforceability, and level of sanctions. It adopts negotiation methods that are acceptable in each region, taking into account differences in cultural background and business practices. It also provides a function to connect with legal experts in the relevant country if international legal proceedings are required. Multilingual support automatically generates appropriate legal documents and removal requests in the local language. A damage claim function that takes exchange rate fluctuations into account also supports international financial negotiations. Statistics on response success rates and effective methods by region are also accumulated and used to continuously improve strategies.

[0063] In at least one embodiment, the time-of-day monitoring function has an adaptive configuration that enables efficient monitoring scheduling based on user activity patterns and regional characteristics. It predicts time periods when unauthorized posting is likely to occur based on information such as the user's daily routine, work hours, area of ​​activity, and events attended, and automatically adjusts the monitoring frequency during those times. It learns differences between weekdays and holidays, daytime and nighttime, and event and normal times, and implements a dynamic monitoring strategy. It also analyzes poster activity patterns and conducts focused monitoring during times when specific posters are most active. An international monitoring system that takes time zones into account enables efficient 24-hour monitoring. During emergencies or special events, it automatically switches to real-time monitoring mode, while during normal times it performs regular monitoring with an emphasis on efficiency. It also takes into account information such as the user's sleep time and meeting times to provide timely notifications. It provides sustainable monitoring services through an optimal monitoring schedule that also takes energy and cost efficiency into account.

[0064] In at least one embodiment, the emotion analysis-based urgency assessment function includes an advanced natural language processing system that automatically assesses the priority of a response based on the content and context of a post. The system comprehensively analyzes text, comments, hashtags, emojis, and other elements associated with a post to estimate the poster's emotions and intentions. Emotional aspects such as malice, ridicule, criticism, praise, and indifference are quantified to automatically assess the urgency of a response. A comprehensive risk assessment is also performed, taking into account factors such as the likelihood of the post spreading, the scope of impact, and the risk of secondary damage. A strong response is immediately taken for posts determined to be high-risk, while a gentler approach is automatically selected for posts determined to be low-risk. The results of the emotion analysis are reported to the user, and advice is provided on measures to address psychological impacts and the need for counseling. Machine learning continuously improves the accuracy of the emotion analysis, enabling highly accurate assessments that take into account cultural backgrounds and differences in linguistic nuances. Urgency assessment history is accumulated and used to quickly respond to similar cases.

[0065] In at least one embodiment, the automatic escalation feature includes a comprehensive configuration that fully automates a tiered response when a removal request is ignored. After a certain period of time has passed since the initial request, the feature automatically transitions to more severe measures, sequentially implementing measures such as a formal removal request with clear legal grounds, reporting the social media operator, contacting legal representatives, and preparing a court petition. The timing of each step can be adjusted based on the user's preferences and the urgency of the case. If the poster responds during the escalation process, the response is automatically adjusted to an appropriate level to avoid excessive measures. Furthermore, the escalation history is recorded in detail and used as evidence in legal proceedings. The feature also takes into account the poster's past response history, providing a longer grace period for cooperative posters and a more rapid escalation for uncooperative posters. Cost-effectiveness is also taken into consideration, and the feature also includes a function to stop escalation above a certain level for minor cases. Users are presented with options and expected outcomes at each step to help them make informed decisions.

[0066] In at least one embodiment, the post content analysis function has an advanced configuration that evaluates the impact on users from various angles based on the detailed content of images and videos. It performs detailed analysis of the image clarity, the user's appearance, facial expressions, clothing, behavior, surrounding circumstances, etc., to quantify the degree of privacy violation. Clearly visible faces, inappropriate photographs, and private scenes are classified as high-risk and prompt action is taken. The function also analyzes the context and purpose of the post, distinguishing between reporting purposes, documenting purposes, and malicious doxxing, and selects the appropriate response method. It also detects whether the image has been altered or not, and takes stronger measures if malicious alterations have been made. It also takes into account the public visibility, number of views, and spread of the post, and implements emergency response if it has already spread widely. The analysis results are reported to users in an easy-to-understand format and can be used to prepare them mentally and determine response strategies. Through continuous learning, the analysis accuracy continues to improve and adapt to new types of posts.

[0067] In at least one embodiment, the related post tracking function includes a comprehensive configuration for continuously monitoring secondary posts and related content derived from a detected post. Detailed tracking of the spread of the original post, including replies, quotes, retweets, and shares, is performed to prevent secondary damage. The function also continuously monitors whether the same image or video is being reposted on other platforms or other accounts. Because related posts are often used in contexts or for purposes different from those of the original post, each post is analyzed and addressed individually. Time series analysis is also used to predict the spread pattern and scope of impact of the post, allowing for early prevention of spread. Appropriate deletion requests are also made to the poster of the related post, enabling comprehensive removal responses. The analysis results of the related posts are also used to evaluate the influence and malicious intent of the original poster and to utilize this information in future response strategies. The monitoring period for related posts can be adjusted by the user, and long-term continuous monitoring is also possible for important cases. The effectiveness of the spread prevention measures is quantitatively evaluated and used to improve response measures.

[0068] In at least one embodiment, the poster behavior prediction function has an advanced configuration that predicts a poster's future behavior based on past behavioral patterns and enables proactive countermeasures. It uses machine learning to analyze a poster's past posting frequency, reaction patterns, response history to removal requests, and activity characteristics on social media to predict future behavior. If a specific poster is likely to repeatedly post similar content, advance warnings and enhanced preventative monitoring are implemented. The function also learns the poster's lifestyle patterns and activity schedules to predict when unauthorized posting is likely to occur. Based on the prediction results, users are provided with advance warnings and advice on behavioral restrictions. It also predicts the likelihood that a poster will comply with a removal request and uses this information to select an effective negotiation strategy. A friendly approach is taken for cooperative posters, and early legal action is taken for uncooperative posters. Prediction accuracy is continuously improved by comparing with actual results, contributing to the optimization of long-term poster management strategies. Improved reliability of the prediction system enables efficient resource allocation and a high response success rate.

[0069] In at least one embodiment, the multi-account monitoring function includes an advanced configuration for comprehensively tracking posts made by the same poster on multiple accounts. It identifies multiple accounts owned by the same person based on characteristics such as the poster's posting patterns, vocabulary, posting time, location information, and device information. It quickly detects cases where a poster who receives a deletion request on one account posts a similar post on another account, enabling a prompt response. It also detects collaboration between multiple accounts and organized harassment, enabling more robust countermeasures. It applies a unified response strategy to all accounts owned by the same poster, enabling effective deletion negotiations. It also determines whether anonymous or pseudonymous accounts are substantially the same through behavioral pattern analysis. Machine learning continuously improves the accuracy of multi-account detection, enabling it to handle sophisticated deception. Furthermore, repeated violations by the same poster can be comprehensively reported to social media operators and combined legal action can be pursued. The management function for detected accounts enables efficient monitoring and response.

[0070] In at least one embodiment, the post diffusion analysis function has a specialized configuration that quantitatively analyzes the impact and diffusion rate of detected posts and determines response priorities. It continuously monitors engagement metrics, such as the number of views, likes, comments, and shares, to track changes in the diffusion status. If the diffusion rate increases rapidly, it automatically switches to emergency response mode and issues faster and stronger removal requests. It also applies special response protocols when a post is spread by an influencer or celebrity. It analyzes the diffusion network to identify key diffusion nodes and develop effective diffusion prevention strategies. It also analyzes diffusion patterns by region, age, gender, etc. to implement targeted responses. It uses predictive models to forecast future diffusion scale and take early prevention measures. The results of the diffusion analysis are reported to users in easy-to-understand graphs and charts, helping them understand the situation and determine response policies. The effectiveness of diffusion prevention measures is also quantitatively evaluated and used to continuously improve response methods.

[0071] In at least one embodiment, the impact assessment system includes a comprehensive configuration that evaluates the specific impact of unauthorized postings on users from multiple angles and determines the appropriate level of response. The degree of damage is quantified from perspectives such as social impact, economic impact, psychological impact, and legal impact. The system calculates individual impact levels by taking into account the user's occupation, social status, public / private distinction, and the content and context of the post. For celebrities and public figures, the system emphasizes social impact, while for ordinary people, the system emphasizes the degree of privacy violation. Regarding economic impact, the system calculates the amount of lost profits due to the use of portrait rights, damages due to defamation, and compensation for mental distress. Based on the results of the impact assessment, the system automatically determines the strength of a deletion request, the need for legal action, and the appropriateness of a claim for damages. The system also tracks changes in impact over time, taking into account factors such as the expansion of damage due to spread and the decline in impact over time. The assessment results are also used as explanatory materials for users to help them understand the situation and decide on future countermeasures. The system also includes a function for expert supervision of the impact assessment, and in complex cases, incorporates human judgment to achieve a comprehensive assessment.

[0072] In at least one embodiment, the custom warning message generation function is highly sophisticated and automatically generates the optimal removal request message based on the poster's characteristics and circumstances. The most effective message is generated by comprehensively analyzing the poster's age, gender, nationality, cultural background, past response history, and the content and context of the post. The level of explanation of the legal basis, the degree of emotional approach, and the manner of expressing force are adjusted depending on the poster. The system automatically selects an educational approach for young posters, a strict legal warning for malicious posters, and a polite message requesting cooperation for well-intentioned posters. Multilingual support allows the system to generate an appropriate message in the poster's native language and incorporate cultural considerations. The system also takes into account the poster's occupation and social status, adjusting the appropriate level of honorific language and use of technical terminology. The effectiveness of the message is tracked, and patterns with a high success rate are learned. Manual adjustments by the user are also possible, allowing customization to reflect personal circumstances or special requests. The generated message can be reviewed by the user before sending, and corrections and approvals are possible as needed.

[0073] In at least one embodiment, the poster communication history management function includes a comprehensive configuration for systematically managing all negotiation records with individual posters. It records in detail, in chronological order, the history of deletion requests sent, responses from the poster, the progress of negotiations, and the final resolution. It references past negotiation experiences with the same poster and utilizes effective and unsuccessful approaches in future negotiations. It also learns the poster's personality traits, negotiation style, and effective persuasive approaches to develop an individually optimized negotiation strategy. It also tracks changes in the poster's cooperation and trustworthiness to identify improvements or deteriorations in the relationship. When the same poster is involved in multiple cases, it also proposes comprehensive solutions and long-term relationship improvement. Communication history can also be used as evidence in legal proceedings, proving the negotiator's good faith or the other party's bad faith. To protect privacy, history information is encrypted and stored only for the minimum necessary period. Users can refer to the history to determine future course of action, and expert advice is also provided.

[0074] In at least one embodiment, the automatic legal document generation function has an advanced configuration that automatically generates various documents required for removal requests and legal proceedings with professional quality. Legal documents such as certified mail, removal requests, damage claims, applications for provisional dispositions, and complaints are automatically generated for each individual case. Legally valid documents are created by integrating information such as the user's personal information, details of the post, the extent of the damage, and applicable laws. Documents appropriate for the applicable jurisdiction are generated, taking into account differences in national laws and document formats. Professional quality is ensured in the use of legal terminology, logical structure, and evidence citation methods. Generated documents undergo review by a lawyer to ensure quality and are adjusted to a level usable in actual legal proceedings. User requests and special circumstances can be reflected, and a wide range of documents are supported, from standardized documents to documents specialized for individual cases. Document generation history is saved and used as reference for similar cases. Document effectiveness is also tracked, and document patterns with high success rates are continuously improved. Generation costs are reasonably set, reducing the financial burden on users.

[0075] In at least one embodiment, the poster trustworthiness evaluation function includes an analytical configuration that predicts a poster's likelihood of cooperation based on their past behavioral history and determines an efficient response strategy. A trust score is calculated by comprehensively evaluating the poster's response history to deletion requests, their response speed, level of cooperation, and commitment fulfillment. A friendly and cooperative approach is automatically selected for posters with high trustworthiness, while a stricter, legally-based approach is automatically selected for posters with low trustworthiness. A multifaceted evaluation is also conducted, taking into account the poster's social attributes, occupation, age, past SNS behavior patterns, and other factors. The trustworthiness evaluation is dynamically updated and adjusted according to changes in the poster's behavior. For posters who demonstrate improving behavior, the trustworthiness is gradually improved, promoting future relationship improvement. The evaluation results are also reported to the user and used to determine negotiation strategies and psychological preparation. The anonymized evaluation data is also used as reference information for other users' cases, contributing to improving the response accuracy of the entire system. To ensure transparency and fairness in the trustworthiness evaluation, the evaluation criteria and calculation method are also disclosed to users.

[0076] In at least one embodiment, the automated settlement negotiation feature includes an advanced negotiation support system that aims to achieve an amicable resolution before legal proceedings. Through direct dialogue with the poster, it automates the negotiation of terms in exchange for removal, the adjustment of damages, and agreement on measures to prevent future recurrence. It proposes realistic and acceptable settlement terms, taking into account the poster's financial situation, social standing, past behavior, etc. The negotiation process involves making incremental concessions and presenting alternatives to seek a mutually acceptable solution. It evaluates the economic rationality of the settlement, taking into account factors such as the cost and time of legal proceedings and the likelihood of success. Negotiation progress is reported to the user in real time, and important decisions are subject to user approval. If a settlement agreement is reached, a legally valid settlement document is automatically generated, and implementation is continuously monitored. Implementation of settlement terms is tracked, and legal action is automatically initiated if any promises are violated. Data on the success rate of settlement negotiations and effective terms is accumulated and used to improve future negotiation strategies.

[0077] In at least one embodiment, the post-deletion monitoring function has a comprehensive configuration that continuously monitors even after deletion is complete to prevent reposting or similar posts. The account of the poster of the deleted post is continuously monitored for a certain period of time to check for similar or retaliatory posts. It also extensively monitors whether the deleted image or video has been reposted on other platforms or accounts. It also checks for deletion from cache sites and archive sites to ensure complete deletion. Even if the poster agrees to the deletion, it monitors their subsequent behavior to check for repeated unauthorized posting of similar content. If reposting or similar posts are discovered, stronger measures are automatically implemented and escalated. The period of post-deletion monitoring is adjusted according to the importance of the issue and the poster's trustworthiness, ensuring efficient resource utilization. Monitoring results are regularly reported to users to provide a sense of security and to consider future countermeasures. Long-term monitoring data is also used to analyze posters' behavioral patterns, contributing to strengthening preventive measures.

[0078] In at least one embodiment, the similar account detection function includes an advanced configuration for early detection of new account creation by problematic posters and activity on related accounts. It identifies multiple accounts owned by the same person based on personal characteristics such as the poster's writing style, posting patterns, vocabulary used, activity times, location information, and device characteristics. It quickly detects cases where a poster who has received a deletion request continues to be active on another account, enabling comprehensive response. It also detects indirect postings using the accounts of family and friends to prevent indirect harassment. Machine learning continuously improves the accuracy of determining the relationship between accounts, addressing even sophisticated impersonation tactics. Detected related accounts are subject to the same level of monitoring as the original account, and a unified response strategy is implemented. Newly created accounts are also automatically identified for their relationship with past problematic posters, and proactive monitoring is conducted. The results of the detection of similar accounts are reported to the user, who is advised on the need for comprehensive countermeasures and effective response methods.

[0079] In at least one embodiment, the poster education function has a constructive mechanism for raising appropriate knowledge and awareness among unauthorized posters. The function automatically generates and provides posters with educational content that clearly explains legal knowledge, such as portrait rights, privacy rights, and the Personal Information Protection Act. The educational content is customized based on the poster's age, occupation, and cultural background to effectively promote understanding. In cases where posts are made out of simple ignorance, an educational approach is emphasized, aiming to prevent similar behavior in the future. The educational content includes specific examples, legal reasons, social impacts, etc., to promote comprehensive understanding. When a poster completes the educational program, the level of future monitoring is reduced and corrective behavior is encouraged. The effectiveness of the education is also measured to evaluate the degree of knowledge retention and behavioral change. The content of the educational program is regularly updated to respond to changes in laws and social conditions. To promote good-will participation, those who complete the education are issued a certificate and social recognition. The education function aims to transform adversarial relationships into cooperative relationships and achieve sustainable problem solving.

[0080] In at least one embodiment, the continuous monitoring alert function includes a comprehensive configuration that periodically reports long-term monitoring status and discovered issues to users. Periodic reports, such as monthly, quarterly, or annual, analyze and report changes in monitored targets, trends in the number of detected cases, changes in response success rates, and new risk factors. Detailed analysis of users' exposure trends, changes in risk levels, effective countermeasures, and areas requiring improvement are performed to support future countermeasure planning. When specific patterns or trends are discovered, an emergency alert is sent immediately to encourage early implementation of countermeasures. The system also proposes adjustments to monitoring strategies based on changes in users' activities and social status. Information on technological advances and changes in the legal environment is also provided to support the adoption of the latest countermeasures. The alert function can be customized to suit the user's level of understanding, from detailed, specialized information to concise, essential information. Long-term patterns discovered through continuous monitoring are used to strengthen preventative measures and develop efficient monitoring methods. Periodic user interviews are also provided to provide ongoing support on how to effectively use the system.

[0081] In at least one embodiment, the poster blocking feature includes a powerful countermeasure system that effectively prevents persistent harassment by malicious posters. It implements a tiered blocking process against posters who continue to ignore deletion requests or who repeatedly post malicious content. The initial stage prioritizes monitoring of posts from the account in question, the middle stage increases the frequency of automatic deletion requests, and the final stage implements comprehensive reporting to social media operators in parallel with legal action. Detailed records are kept of the blocked individual's account information, posting patterns, and related accounts, and circumvention attempts such as the creation of new accounts are also detected. Retaliation by blocked individuals and indirect harassment using third parties are also monitored. The effectiveness of the blocking process is continuously evaluated, and the level of countermeasures is adjusted as necessary. Similar reports from other users are also considered, and measures against organized harassment and group attacks are strengthened. The application of the blocking function is carefully considered, and a review function is also included to avoid unjustified restrictions due to false positives. Users are provided with detailed reports of the blocking situation and receive ongoing support to ensure safety and implement future measures.

[0082] In at least one embodiment, the preventive warning system has an advanced configuration that predicts risks before unauthorized posting occurs and supports the implementation of preventive measures. It proactively identifies situations with a high risk of unauthorized photography based on information such as a user's activity schedule, upcoming events, and public plans. It provides advance warnings and advice on preventive measures for planned attendance at concerts, sporting events, public gatherings, etc. It also monitors the activities of posters who have previously posted unauthorized content and urges special caution if they are expected to attend the same event. As preventive measures, it provides specific guidelines for action, such as contacting event organizers in advance, requesting cooperation from participants, and confirming areas where photography is restricted. Depending on the risk level, it automatically adjusts measures such as strengthening monitoring on the day, increasing the frequency of real-time detection, and preparing an emergency response system. The effectiveness of preventive warnings is evaluated after the fact and used to improve the accuracy of the warning system. The effectiveness of user behavior changes and the effectiveness of preventive measures in preventing unauthorized posting are also quantitatively analyzed. This preventive approach reduces the burden of post-event responses and increases users' sense of security.

[0083] In at least one embodiment, the poster history analysis function includes an advanced configuration that builds effective response strategies through comprehensive behavioral analysis of individual posters. Detailed analysis is performed on the poster's entire past posting history, responses to deletion requests, activity patterns on social media, and relationships with other users. Trends in posting content, changes in frequency, response patterns, and signs of improvement or deterioration are tracked over time to improve the accuracy of behavioral predictions. Background information, such as the poster's occupation, age, residential area, and social attributes, is also taken into account to determine a response approach tailored to individual characteristics. For posters who have been cooperative in the past, emphasis is placed on building trust, while for posters who have been uncooperative, strict measures, including legal action, are selected. Historical analysis also estimates the poster's motives and intentions, providing information for determining whether to take an educational or legal approach. The analysis results are also used as reference information for other similar cases, contributing to improved response accuracy across the entire system. Accumulating historical data also tracks the poster's long-term behavioral changes and evaluates the long-term effectiveness of countermeasures. To protect privacy, historical information is appropriately anonymized and stored only for the minimum necessary period.

[0084] In at least one embodiment, the comprehensive report generation function has an integrated configuration that comprehensively analyzes the overall effectiveness and areas for improvement of privacy protection activities. It performs detailed analysis of monitoring performance over the entire period since system implementation, changes in detection accuracy, trends in response success rates, changes in user satisfaction, etc., and generates periodic comprehensive reports. It conducts comprehensive evaluations that include technical improvements, operational issues, and responses to changes in the legal environment. At the individual user level, it provides detailed reports on the effectiveness of privacy protection, changes in risk levels, successful countermeasures, and future improvement proposals. At the industry level, it also provides trend analysis of similar cases, sharing of effective countermeasures, and early warning of new threats. Reports can be customized based on the user's level of expertise and are provided in a variety of formats, from strategic summaries for executives to detailed analyses for engineers. It also provides objective evaluations that include third-party audit results and international comparative data. The comprehensive report supports continuous system improvement and user strategic decision-making, contributing to the realization of long-term privacy protection. Technology independent design

[0085] In at least one embodiment, a technology-agnostic architecture enables a comprehensive system design with flexibility and scalability that is independent of specific technology products or vendors. This system employs a configuration that dynamically selects and switches between optimal combinations from multiple options in each technology domain, including artificial intelligence and machine learning, sensors, communications, display, data processing, and security. Each technology component is loosely coupled via a standardized interface, allowing individual technology elements to be updated and replaced independently. Technology selection is automatically optimized based on a variety of evaluation criteria, including performance requirements, cost constraints, usage environment, security level, and legal requirements. To respond to the emergence of new technologies and advancements in existing technologies, the system also incorporates an automated framework for technology evaluation, implementation, and migration. This design avoids the risk of dependency on specific technologies and ensures adaptability to long-term technological innovations.

[0086] In at least one embodiment, the artificial intelligence / machine learning technology selection system has a flexible configuration that dynamically selects the optimal method from a variety of AI algorithms depending on the application. In deep learning, selectable algorithms include convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTMs), gated recurrent units (GRUs), transformers, attention mechanisms, generative adversarial networks (GANs), variational autoencoders (VAEs), and diffusion models. In traditional machine learning, selectable algorithms include support vector machines (SVMs), random forests, gradient boosting, decision trees, naive Bayes, k-means clustering, principal component analysis (PCA), linear regression, and logistic regression. Advanced techniques such as reinforcement learning, transfer learning, meta-learning, federated learning, online learning, and ensemble learning are also supported. As for AI frameworks, it integrates TensorFlow, PyTorch, Keras, scikit-learn, Apache MXNet, Caffe, Theano, ONNX, etc. in an interoperable manner.

[0087] In at least one embodiment, the sensor technology integration platform provides a comprehensive architecture for unified control and utilization of a wide variety of sensor devices. Image sensors can be selected from a variety of technologies, including CCD sensors, CMOS sensors, BSI sensors, stacked sensors, organic thin-film sensors, quantum dot sensors, and graphene sensors. 3D measurement can be performed using a combination of Time of Flight (ToF) sensors, LiDAR sensors, stereo cameras, structured light sensors, laser range finders, ultrasonic sensors, and millimeter-wave radar, depending on the application. For voice input, a selection of condenser microphones, dynamic microphones, MEMS microphones, piezoelectric microphones, optical microphones, laser microphones, bone conduction microphones, and beamforming microphone arrays can be made depending on the environment. Environmental sensors, including temperature sensors, humidity sensors, barometric pressure sensors, illuminance sensors, ultraviolet sensors, infrared sensors, gas sensors, vibration sensors, and magnetic sensors, can also be integrated to achieve comprehensive environmental recognition. The output of each sensor is converted into a standardized data format, making it transparently available to upper-layer applications.

[0088] In at least one embodiment, the communication technology selection engine includes an adaptive configuration that dynamically evaluates and selects available communication methods to ensure the optimal communication path. Wireless communication technologies include 5G (Sub-6 GHz, millimeter wave), 4G LTE, 3G, WiFi 6 / 6E / 7, Bluetooth 5.0 or later, ZigBee, LoRaWAN, NFC, NB-IoT, Sigfox, Thread, Matter, satellite communications (LEO, MEO, GEO), quantum communications, etc. Wired communications include Ethernet (10 Mbps-400 Gbps), USB (2.0-4.0), Thunderbolt (3-5), HDMI (registered trademark), DisplayPort, optical fiber (single mode, multimode), power line communications, serial communications, etc. At the communication protocol level, TCP / IP, UDP, HTTP / HTTPS, WebSocket, gRPC, MQTT, CoAP, AMQP, XMPP, etc. are selected depending on the situation. It also supports a variety of encryption methods for communications, including TLS 1.3, WPA3, AES, RSA, elliptic curve cryptography, and quantum cryptography, and automatically selects the optimal combination based on security level and performance requirements.It also has a function that dynamically changes the optimal communication route in real time by monitoring network quality.

[0089] In at least one embodiment, the display and output technology integration system has a flexible configuration that provides a versatile rendering engine compatible with a variety of output devices. Visual display technologies include LCD (TN, IPS, VA), OLED (AMOLED, PMOLED), QLED, Mini LED, Micro LED, E-ink, electronic paper, projectors (DLP, LCD, LCOS, laser), holographic displays, aerial projection displays, and retinal projection displays. Resolutions include existing standards such as 8K, 4K, QHD, Full HD, HD, and VGA, as well as future ultra-high resolutions such as 16K and 32K. Refresh rates include 60Hz, 120Hz, 144Hz, 240Hz, and variable refresh rates (VRR, FreeSync, G-Sync). The system also supports augmented reality (AR), virtual reality (VR), and mixed reality (MR) devices, and can integrate next-generation display devices such as HMDs, smart glasses, and contact lens displays. For audio output, a combination of technologies including stereo, 5.1 / 7.1 / 9.1 surround, Dolby Atmos, DTS:X, binaural audio, bone conduction, directional speakers, and ultrasonic speakers is used to provide a highly immersive audio experience.

[0090] In at least one embodiment, the database and storage technology selection system includes advanced configuration for dynamically selecting the optimal storage solution based on the data characteristics and usage. Relational databases include MySQL®, PostgreSQL, Oracle Database, Microsoft SQL Server, IBM Db2, SQLite, and other options. NoSQL databases include MongoDB (document-based), Cassandra (column-based), Redis (key-value), Neo4j (graph-based), Amazon DynamoDB, and Apache CouchDB, depending on the usage. Special-purpose databases include time-series databases (InfluxDB, TimescaleDB), search engines (Elasticsearch, Apache Solr), distributed file systems (Hadoop HDFS, Apache Kafka), and blockchains (Ethereum, Hyperledger). Storage media include SSDs (SATA, NVMe, PCIe), HDDs, optical disks, magnetic tape, flash memory, phase-change memory, and resistive memory, which are hierarchically organized and efficiently utilized. By collaborating with cloud storage services (Amazon S3, Google Cloud Storage, Microsoft Azure Blob), we are able to provide scalable and highly durable data storage.

[0091] In at least one embodiment, the security technology integration framework has a robust configuration that ensures comprehensive security through a multi-layered defense approach. Encryption technologies include symmetric key cryptography (AES-128 / 192 / 256, ChaCha20), asymmetric key cryptography (RSA, elliptic curve cryptography, Ed25519), hash functions (SHA-256 / 384 / 512, Blake2, Argon2), key derivation functions (PBKDF2, scrypt), quantum-resistant cryptography, and other technologies selected according to the situation. Authentication technologies include a combination of passwords, multi-factor authentication (MFA), biometric authentication (fingerprint, face, iris, voiceprint, vein), digital certificates, FIDO2 / WebAuthn, OAuth 2.0, OpenID Connect, SAML, and other technologies. Network security includes firewalls, IDS / IPS, VPNs (IPsec, WireGuard, OpenVPN), zero-trust architecture, SASE, and DDoS protection. In addition, operational security such as vulnerability management, penetration testing, security audits, and incident response will be automated to maintain a continuous security level. Advanced privacy protection techniques such as differential privacy, homomorphic encryption, and secure multi-party computation have also been introduced.

[0092] In at least one embodiment, the cloud infrastructure technology selection platform provides a comprehensive configuration that unifies management of various cloud service providers and deployment types. For public clouds, users can select the optimal service from major providers such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), IBM Cloud, Oracle Cloud Infrastructure, Alibaba Cloud, and Tencent Cloud. For private clouds, platforms such as VMware vSphere, OpenStack, Microsoft System Center, and Citrix XenServer are utilized. For hybrid cloud and multi-cloud environments, multiple cloud environments are managed in an integrated manner to achieve optimal workload placement. Container technologies such as Docker, Podman, and containerd are used, and orchestration technologies such as Kubernetes, Docker Swarm, and Apache Mesos are used. Serverless technologies such as AWS Lambda, Azure Functions, Google Cloud Functions, and Cloudflare Workers are used to ensure efficient resource utilization. Geographically distributed, high-performance services are provided using edge computing, fog computing, and CDNs (Content Delivery Networks).

[0093] In at least one embodiment, the mobile device framework has a flexible configuration that unifies support for various mobile platforms and device types. It supports major mobile operating systems, including iOS, Android, Windows Mobile, HarmonyOS, and KaiOS. It also supports a variety of wearable devices, including smartphones, tablets, smartwatches, fitness trackers, smart glasses, earphones / headphones, and smart rings. Application development can be performed using native development (Swift / Objective-C, Kotlin / Java), cross-platform development (React Native, Flutter, Xamarin, Cordova / PhoneGap), and progressive web apps (PWAs). Access to hardware features is unified, allowing for the use of various sensors and communication functions, including cameras, microphones, GPS, accelerometers, gyroscopes, magnetometers, proximity sensors, ambient light sensors, barometers, NFC, Bluetooth, and Wi-Fi. It also provides an optimal user experience through dynamic processing load adjustment based on device performance characteristics (CPU, memory, storage, and battery).

[0094] In at least one embodiment, the operating system abstraction layer provides a comprehensive compatibility system that ensures consistent operation across diverse operating system platforms. Desktop operating systems include Windows (10, 11, and later), macOS (Monterey and later), Linux (Ubuntu, CentOS, Red Hat, SUSE, Debian, Arch Linux, etc.), and Unix-based operating systems (FreeBSD, OpenBSD, and Solaris). Server operating systems include enterprise systems such as Windows Server, Linux Server, AIX, and HP-UX. Real-time operating systems include FreeRTOS, QNX, VxWorks, and RT-Linux. In virtualized environments, the layer ensures operation on various hypervisors, including VMware ESXi, Microsoft Hyper-V, Citrix XenServer, KVM, and VirtualBox. To accommodate differences in operating system functionality, the layer provides an abstraction mechanism that transparently handles differences in file systems (NTFS, APFS, ext4, XFS, ZFS, etc.), process management, memory management, networking, and security features. This design enables highly portable application development and operation that is independent of the operating system.

[0095] In at least one embodiment, the programming language and runtime integration system provides a flexible development environment that unifies the management of implementations in various programming languages. Compiled languages ​​include C, C++, Rust, Go, Swift, Kotlin, Java, C#, Scala, Haskell, and OCaml. Interpreted languages ​​include Python, JavaScript, TypeScript, Ruby, PHP, Perl, Lua, and R. Special-purpose languages ​​such as functional languages ​​(Lisp, Clojure, Erlang, Elixir, and F#), logic languages ​​(Prolog), and domain-specific languages ​​(SQL, MATLAB®, and Mathematica) are also integrated. Runtime environments utilize the .NET Framework / .NET Core, Java Virtual Machine (JVM), Node.js, Python Runtime, the V8 engine, and WebAssembly (WASM). To ensure interoperability between languages, it employs standard serialization formats such as JSON, XML, Protocol Buffers, Apache Avro, and MessagePack, and achieves language-independent communication through interfaces such as RESTful API, GraphQL, and gRPC. It also automatically applies optimizations (memory management, parallel processing, type safety, etc.) that take advantage of the characteristics of each language, achieving high-performance system integration.

[0096] In at least one embodiment, the development framework and library integration platform has a comprehensive configuration that unifies management of various development tools and libraries, enabling flexible selection of technology stacks. Web development frameworks include React, Vue.js, Angular, Svelte, Next.js, Nuxt.js, Express.js, Django, Flask, Ruby on Rails, Spring Boot, and ASP.NET Core. Mobile development supports cross-platform technologies such as React Native, Flutter, Xamarin, Ionic, and Apache Cordova. Data processing and analysis integrates scientific computing and machine learning libraries such as Apache Spark, Apache Flink, Pandas, NumPy, SciPy, TensorFlow, PyTorch, and scikit-learn. UI and UX frameworks support design systems such as Bootstrap, Tailwind CSS, Material-UI, Ant Design, Semantic UI, and Foundation. The development efficiency tool also integrates build tools and test frameworks such as Webpack, Parcel, Vite, Babel, ESLint, Prettier, Jest, and Cypress to support modern development workflows. Development operations processes such as version control, dependency management, and continuous integration are also automated.

[0097] In at least one embodiment, the API and protocol integration system provides a comprehensive configuration that unifies various communication protocols and API styles, ensuring interoperability. Different API styles, such as REST API, GraphQL, gRPC, SOAP, WebSocket, and Server-Sent Events (SSE), can be used together within the same system. Data exchange formats include JSON, XML, YAML, TOML, CSV, Protocol Buffers, Apache Avro, MessagePack, and CBOR, depending on the situation. Authentication and authorization protocols include OAuth 2.0, OpenID Connect, SAML, JWT, API Key, Basic Authentication, and Digest Authentication. Messaging and event streaming services include Apache Kafka, RabbitMQ, Apache Pulsar, Amazon SQS, Redis Pub / Sub, MQTT, and AMQP. API management features include rate limiting, caching, load balancing, API gateways, service meshes (Istio, Linkerd), and automatic OpenAPI specification generation. Additionally, stability is ensured during system updates through API versioning, maintaining backward compatibility, and gradual migration (Blue-Green Deployment, Canary Release), etc. It also has the ability to automatically determine the performance characteristics and application scenarios of each protocol and dynamically select the optimal communication method.

[0098] In at least one embodiment, the hardware abstraction and optimization system provides a comprehensive architecture that supports diverse hardware configurations and maximizes performance. It supports different CPU architectures, including x86-64 (Intel, AMD), ARM (Cortex-A, Apple Silicon), RISC-V, MIPS, PowerPC, and SPARC. It leverages parallel computing technologies, such as NVIDIA CUDA, AMD ROCm, Intel oneAPI, OpenCL, OpenMP, and MPI, for GPU and parallel processing. It supports dedicated chip accelerators, including FPGAs (Xilinx, Intel Altera), ASICs, DSPs, NPUs (Neural Processing Units), TPUs (Tensor Processing Units), and VPUs (Vision Processing Units). It efficiently utilizes diverse memory hierarchies, including DDR4 / DDR5 RAM, HBM (High Bandwidth Memory), NVMe SSDs, Optane memory, MRAM, and ReRAM. It is also prepared to support next-generation computing technologies, such as quantum processors, optical computers, and neuromorphic chips. Dynamic monitoring of hardware performance optimizes temperature, power consumption and processing load, enabling automatic clock adjustment, power management and thermal management.

[0099] In at least one embodiment, the future-ready and progress-tracking system includes advanced configurations that ensure continuous adaptability to technological innovations. In quantum computing, we are prepared to support different quantum computing paradigms, including gate-based quantum computers, annealing quantum computers, and topological quantum computers. In next-generation communications technologies, we plan to support 6G, terahertz communications, visible light communications, quantum internet, and satellite constellations. In emerging AI technologies, we continuously monitor research trends in artificial general intelligence (AGI), neuromorphic computing, swarm intelligence, evolutionary computing, and quantum machine learning, building a system for rapid integration into practical applications. We are also considering biotechnology integration technologies such as DNA storage, biosensors, and brain-computer interfaces. Furthermore, our technology forecasting system analyzes paper publications, patent applications, and R&D trends to automate the early identification and evaluation of promising technologies. A framework for prototype development, proof-of-concept, and phased implementation ensures the safe and efficient integration of new technologies.

[0100] In at least one embodiment, the technology update and migration management system has an advanced configuration that allows for gradual updates of technology elements while continuing system operations. Version control uses semantic versioning, branching strategies (Git Flow, GitHub Flow), tag management, and other methods to manage systematic updates of technology components. Phased migration minimizes risk by using techniques such as blue-green deployment, canary release, rolling update, and feature toggle. Compatibility management maintains consistency with existing systems through features such as API versioning, schema evolution, data migration, and legacy system integration. An automated testing framework automatically executes unit tests, integration tests, system tests, performance tests, and security tests to prevent quality degradation due to updates. A rollback function allows for rapid restoration to the original state in the event of a problem. Continuous monitoring of technology evaluation metrics (performance, stability, security, maintainability, cost, etc.) quantitatively evaluates the effectiveness and impact of updates. Furthermore, update history, impact analysis, and best practices are accumulated to improve organizational technology management capabilities.

[0101] In at least one embodiment, the interoperability and standardization management system provides a comprehensive integration framework that ensures seamless collaboration between different technologies. International standards are actively adopted to ensure interoperability through standards organizations such as ISO / IEC, IEEE, IETF, W3C, OASIS, and ITU-T. Industry standards include de facto standards such as OpenAPI, OAuth, SAML, LDAP, SNMP, JDBC, and ODBC. Data format standards include metadata standards such as JSON Schema, XML Schema, RDF, OWL, and Dublin Core, ensuring semantic consistency. Protocol conversion functions transparently handle automatic conversion between different communication protocols, data format conversion, and encoding conversion. Design patterns such as the adapter, bridge, and facade patterns abstract technical differences. Continuous monitoring of standards compliance and plans for new standards maintain long-term interoperability. Even when integrating open source and proprietary software, proper integration is achieved while meeting license compliance and legal requirements.

[0102] In at least one embodiment, the technology evaluation and selection automation system is configured to provide a comprehensive evaluation framework to support technical decision-making. Performance evaluation involves automatically measuring quantitative indicators such as processing speed, throughput, latency, memory usage, CPU usage, and network bandwidth, and conducting benchmark comparisons. Quality evaluation involves a multifaceted analysis of non-functional requirements such as reliability, availability, maintainability, scalability, security, and usability. Cost analysis involves a comprehensive evaluation of initial implementation costs, operating costs, license costs, human resources, opportunity costs, and other factors. Risk evaluation involves analyzing technical risks, vendor lock-in, end of support, security vulnerabilities, legal restrictions, and other factors to generate a risk matrix. Strategic fit evaluation involves determining consistency with an organization's technology strategy, business requirements, and future plans. A predictive model utilizing machine learning also evaluates the technology's future potential, maturity, and expected adoption. Evaluation results are visualized as a multi-dimensional decision-making matrix, supporting consensus building among stakeholders. Accumulating evaluation history also allows for refinement of organization-specific evaluation criteria and improved decision-making quality.

[0103] In at least one embodiment, the legacy system integration and phased migration platform provides a comprehensive architecture for gradual modernization while respecting existing systems. Integrating with legacy technologies provides connectivity with older languages ​​such as COBOL, FORTRAN, and Assembly, as well as mainframes, midrange computers, and older databases (IMS, VSAM, etc.). A protocol conversion gateway bridges legacy communication protocols (SNA, IPX / SPX, NetBIOS, etc.) with modern protocols. Data migration tools support safe and reliable data migration through features such as conversion between different data formats and encodings, data cleansing, quality verification, and incremental synchronization. Phased replacement utilizes design patterns such as the strangler pattern and anti-corruption layer to minimize risk. The platform also supports the development of migration plans through functional analysis of legacy systems, dependency mapping, and impact assessment. To ensure operational continuity during the migration period, it also provides features such as parallel operation, phased switchover, and emergency rollback. Organizational change management also includes support for user training, process improvement, and documentation.

[0104] In at least one embodiment, the open source community collaboration system has a comprehensive configuration that enables collaborative development with the technology ecosystem through the use and contribution of open source software. Collaboration with major open source projects (Linux®, Apache, CNCF, Eclipse, Mozilla, etc.) establishes a system for continuously incorporating the latest technological trends. License management automatically monitors the requirements of various licenses, such as GPL, MIT, Apache, and BSD, to prevent compliance violations. Vulnerability management monitors the CVE database, GitHub Security Advisories, and various security information sources to continuously evaluate the security risks of open source components. Community contributions include bug fixes, feature additions, and documentation improvements, contributing to the development of the entire ecosystem. Furthermore, the open sourcing of useful internally developed technologies and tools contributes to raising the technical standard of the industry as a whole. When selecting technologies, evaluation criteria include community activity, continuity of development, and corporate support status, ensuring sustainable technology selection. An appropriate combination of open source and proprietary software aims to achieve both cost performance and technical quality.

Claims

1. A privacy protection system comprising a user information registration unit that registers a user's biometric feature information, a monitoring unit that collects public posts from SNS platforms, and a match detection unit that detects whether the user is reflected in the collected posts, wherein the biometric feature information includes a plurality of features selected from facial image features, voice features, body shape features, and movement features.

2. 2. The privacy protection system of claim 1, The privacy protection system is characterized in that the user information registration unit registers the user's 3D body scan and features generated from existing photos using machine learning.

3. 2. The privacy protection system of claim 1, A privacy protection system characterized in that the match detection unit has a machine learning function that predicts changes in a user's appearance and improves detection accuracy.

4. 2. The privacy protection system of claim 1, The privacy protection system further comprises a message generation unit and a transmission unit that generate a deletion request message for the detected post and transmit the message to the poster or the SNS platform.

5. A privacy protection system according to claim 4, A privacy protection system further comprising a negotiation unit that negotiates with the poster and takes gradual measures depending on the response status to the deletion request.

6. 1. A computer-implemented privacy protection method, comprising: A privacy protection method comprising the steps of registering a user's biometric feature information, collecting public posts from a social networking platform, and detecting reflections of the user from the collected posts, wherein the biometric feature information includes a plurality of features selected from facial image features, voice features, body shape features, and movement features.

7. 7. The privacy protection method according to claim 6, The privacy protection method is characterized in that the registration step includes a step of registering a feature vector generated from the user's 3D body scan and existing photos using machine learning.

8. On the computer, A program that functions as a means for registering a user's biometric feature information, a means for collecting public posts from a social networking platform, and a means for detecting reflections of the user from the collected posts, wherein the biometric feature information includes a plurality of features selected from facial image features, voice features, body shape features, and movement features.

9. The program according to claim 8, The program is characterized in that the registration means includes means for registering feature vectors generated from a user's 3D body scan and existing photos using machine learning.

10. The program according to claim 8, A program characterized by functioning as a means for generating a deletion request message for a detected post and sending it to the poster or the SNS platform, and as a means for negotiating with the poster and taking gradual response measures depending on the response to the deletion request.

11. A privacy protection system comprising a user information registration unit that registers a user's biometric feature information, a monitoring unit that collects public posts from SNS platforms, and a match detection unit that detects whether the user is reflected in the collected posts, wherein the biometric feature information includes a plurality of features selected from facial image features, voice features, body shape features, and movement features.