622 results about "Watermark" patented technology

Systems and methods disclosed herein automatically authorize, audit, and manage usage of protected digital content via agentic artificial intelligence (AI) models. A data access / usage request is received (e.g., from a graphical user interface) that is associated with digital assets licensed from third parties. The system uses a first AI agent set to identify the digital content and retrieve corresponding access policies from a distributed database. The system uses a second AI agent set (same as or different from the first AI agent set) to evaluate the request against the retrieved policy to generate a permission set and / or settlement instructions. The system uses a third AI agent set (same as or different from the first and / or second AI agent sets) to embed digital watermarks and / or cryptographic signatures into the accessed content, and to record an audit trail of access, authorization, and / or settlement events in a distributed ledger or database.

The invention discloses an active defense method and system based on a large model, and relates to the technical field of security protection, and the method comprises the steps: intercepting a malicious request of an external attacker, cleaning sensitive information and adversarial samples in the malicious request, and outputting standardized data; injecting the standardized data as training data into a training confrontation sample to optimize a protection model, and ensuring the leakage traceability of the protection model by embedding a digital watermark; and trapping an attacker by deploying a honey spot interface and triggering a countering strategy, generating a dynamic defense rule by using the protection model, and updating the training confrontation sample in real time for continuous optimization of the protection model. Active attack sensing and advanced attack blocking are achieved through malicious request interception cleaning and honey spot trapping countering, dynamic defense rule generation and protection model continuous optimization are combined to adapt to attack iteration, a digital watermark tracing mechanism is matched, an'interception-protection-optimization 'closed-loop full link is constructed, and the security defense capability of the protection model is improved.

The invention discloses a dynamic portrait construction method and system fusing a large model and user behavior data, belongs to the technical field of artificial intelligence and big data analysis, and aims to solve the problems of insufficient real-time performance, difficulty in multi-source data integration and high privacy risk in the traditional technology. The method comprises the following steps: collecting basic attributes, behavior sequences and unstructured data by burying points, and processing through an Apache Flink session window and a dynamic watermark; multi-modal feature extraction (discrete feature embedding, bidirectional LSTM coding behavior sequence and BERT coding text) is carried out, and joint embedding is generated through cross-modal contrast learning; generating three types of labels, namely a static label (rule engine), a dynamic label (1.3 B parameter quantity Nano-vLLM) and a predictive label (XGBoost), and dynamically adjusting weights; and realizing global model updating through federated learning and differential privacy. The system comprises a data acquisition layer, a feature extraction layer and a label generation updating layer. The real-time performance and accuracy of the portrait are improved, the privacy of the user is protected, and the commercial value in e-commerce, finance and other scenes is remarkable.

The invention provides a multi-stage desensitization electricity charge sensitive data protection system, belongs to the technical field of information security in the power industry, and relates to a full-life-cycle protection scheme of sensitive data such as an identity label, account information and contact information in an electricity charge service system. The problems that in the prior art, only simple masking or full-table encryption is carried out on a database layer, the desensitization dimension is single, multiple links are prone to leakage, no role fine-grained desensitization strategy exists, and exported files are difficult to trace are solved. The system comprises a data acquisition source and acquisition layer desensitization, a transmission layer encryption, a storage layer transparent encryption, an API gateway, a desensitization strategy center, a front-end dynamic mask, a watermark export, a log desensitization plug-in and an auditing log module, covers the whole process from data acquisition to log auditing, dynamically regulates and controls data display according to roles, and exports a file embedded identity watermark. And desensitizing the log and reserving operation marks. Full-link leakage prevention, fine-grained permission control and leakage traceability can be realized, and the transformation cost is low.

The invention discloses an image watermarking method based on a space channel interactive attention mechanism. The image watermarking method mainly comprises the following steps: acquiring an original image and constructing an image watermarking network based on the space channel attention mechanism; inputting the original image and the watermark into a watermark-containing image generation framework to obtain a watermark-containing image; inputting the image with the watermark into an image processing noise layer to obtain a noise image; inputting the noise image into a watermark extraction framework to obtain an extracted watermark; and constraining the training of the whole image watermark network based on the space channel attention mechanism by using the total loss. The image watermark network based on the space channel attention mechanism is used for copyright protection, and high-capacity embedding of watermarks, high-quality generation of images with watermarks and high-robustness extraction of the watermarks are achieved. According to the method, a depth feature map of the watermark is generated through watermark dimension extension, remodeling and diffusion by using a multi-layer sensor and the like. Meanwhile, the feature retention loss can promote the optimization of the total loss on the network training.

A frictionless checkout system identifies items in retail transactions using multiple cameras and image processing. Ceiling-, bagging area- and / or shelf-mounted cameras capture video frames of items in a shopping cart from different perspectives to form an initial list of items associated with a shopper. A bagging-area camera captures video frames as items are removed from the cart and placed into bags. An image processing system, comprising object segmentation, digital watermark reading, and complementary methods such as barcode detection and object recognition, identifies the items and updates a transaction tally. Prior to unloading, the system maintains a global state of items and their positions in the cart. As items are removed, changes in this state are detected and verified at the bagging area. The system provides real-time identification, reduces manual scanning, and generates alerts when items detected in the cart are not added to the transaction tally.

The invention discloses a vision enhancement robust digital dark watermarking method based on deep learning, a storage medium and equipment, and belongs to the technical field of digital image processing and information security. According to the method, a visual enhancement module comprising a self-adaptive watermark region adjustment module and a frequency enhancement module is constructed, and a multi-region local loss training mechanism and a screen shooting simulation module are combined, so that the visual quality of a watermark image is improved, and meanwhile, the robustness of the watermark image for resisting physical attacks such as screen shooting is enhanced. The specific processing flow comprises the following steps: acquiring an original image and watermark information; embedding the watermark information into the image by using an encoder, wherein an embedded region is optimized by a self-adaptive region guide matrix generated based on the image edge and gray information; in the model training process, a noise layer simulating screen shooting physical distortion is introduced, and the area weight is dynamically adjusted according to residual error distribution in the later stage of training so as to focus and optimize the image quality; watermark information is extracted from an image which may suffer from an attack by using a decoder.

The invention discloses a test spline identity tracing method and system based on a block chain. The method comprises the following steps: collecting full-life-cycle multi-modal data of a test spline embedded with a PUF chip for quality evaluation and semantic mapping; generating an attack judgment mark and an abnormal conduction path so as to embed an encrypted watermark in the control instruction; carrying out block chain evidence storage on the standardized traceability data set; constructing a test spline dynamic knowledge graph to generate a knowledge enhancement traceability data set; analyzing a control instruction stream carrying a watermark, monitoring a deviation value between an execution result and an expected physical behavior, generating an execution deviation value and watermark feedback data, enhancing a traceability data set in combination with base knowledge, generating attack source coordinate information and a traceability path map, and pushing a traceability report which cannot be tampered. The space-time calibration of the multi-source heterogeneous data is realized, and the integrity and consistency of the traceability data are ensured; a PUF chip is adopted, and watermark information which cannot be tampered is embedded in a control instruction, so that double protection from a physical layer to a data layer is realized.

The invention relates to the technical field of three-dimensional Gaussian scene watermarking, in particular to a panoramic watermark processing method and device for a three-dimensional Gaussian scene, equipment and a medium. Determining the parameter sensitivity of each first Gaussian unit; screening a second Gaussian unit of which the corresponding parameter sensitivity is greater than a preset parameter sensitivity threshold from all the first Gaussian units; and embedding the copyright message in the second Gaussian unit in the three-dimensional Gaussian scene, thereby completing the embedding operation of the panoramic watermark. According to the embodiment of the invention, the parameter sensitivity of the first Gaussian unit is estimated through the two-dimensional original image and the first rendered image of different visual angles, so that the geometric structure characteristics of the three-dimensional scene are considered when the watermark is embedded, and the watermark information distortion is avoided.

The invention provides a screen hidden watermark extracting and tracing method and system, a storage medium and electronic equipment, and relates to the technical field of image processing. According to the technical scheme provided by the invention, the copied picture is divided into the plurality of grid units with the same size according to the screen parameters, and the overall picture with the original uneven quality is converted into the local area which can be independently evaluated. And the watermark information is screened through the watermark recognition confidence, and good target grid units are reserved, so that the negative influence of a low-quality region on the overall analysis result is avoided. The local watermark information is fused according to the splicing positions of the multiple adjacent target grid units, the problem that information of a single area is incomplete is solved through area cooperation, and the integrity and accuracy of global watermark information are improved. Through layer-by-layer progressive processing of regionalization processing, quality screening, collaborative fusion and equipment optimization, the accuracy of watermark identification is significantly improved, and the reliability of traceability analysis is further improved.

The systems and methods disclosed herein embed and store traceable watermarks across multiple data modalities including text, image, audio, video, and structured data. The systems and methods disclosed herein receive an input dataset and generate unique watermark patterns for each data modality using cryptographic hash functions applied to dataset identifiers. The watermark patterns include parameters that provide instructions to watermark the input dataset. Watermarking includes modifying discrete data values, relationships, or arrangements within the original dataset at predetermined locations. The watermarked dataset is used to generate a hierarchical fingerprint structure including multiple levels of cryptographic hash identifiers that represent different portions of the data (e.g., at varying granularities). Both the watermark patterns and hierarchical fingerprints are stored in a distributed database accessible through a decentralized network, thus enabling authorized computing devices to verify data provenance and detect potential misappropriation across heterogeneous digital content types.

A QR Code Verification Engine provides a multi-layered security framework for generating, validating, and authenticating QR codes while preventing tampering, fraud, and unauthorized access. The system embeds a hidden security layer within the QR code using steganographic encoding or invisible watermarking techniques, ensuring detection of any modifications. The hidden layer is encrypted using asymmetric cryptography, allowing only an authorized verification system to extract and validate it. An AI-powered tamper detection module analyzes QR codes for anomalies, while cryptographic hash verification ensures integrity. The system employs biometric authentication, push notification approvals, and contextual security measures to enhance user verification. Dynamic QR codes with expiration rules prevent replay attacks. Secure offline verification allows authentication without network connectivity. The system integrates with financial platforms, web security tools, and real-time fraud detection mechanisms, ensuring a highly secure and scalable QR code validation framework for transactions, identity verification, and access control applications.

The invention discloses a cloud platform automatic inspection method and system based on multi-dimensional intelligent analysis. By collecting resource metadata, performance indexes, logs and change events, a unified event object containing resource identifiers, event timestamps, association keys and credibility scores is generated, and out-of-order rearrangement and layered missing compensation are completed based on event time water level lines. Second-level and minute-level multi-granularity dynamic baselines are constructed for the key indexes, drift detection is carried out, and the exception score is calculated by fusing the super-boundary amplitude, the change rate, the duration and the cross-index consistency. And constructing a resource dependence topology with credibility and aging attenuation, introducing a time-delay consistency constraint to carry out contribution degree attribution and cut candidate root causes, fusing a Bayesian network and a fault knowledge graph and combining a historical fault library to update a prior probability positioning root cause on line, and outputting an interpretable link. Implempotent self-healing execution, acceptance and rollback closed loop are realized according to risk access control, the positioning accuracy is improved, and the fault recovery time is shortened.

Methods and apparatus for end-to-end unsupervised multi-document blind image denoising is presented. The multi-document blind image denoiser removes various noise types from noisy documents without paired target cleaned documents and preserves the contents for optical character recognition. The end-to-end unsupervised multi-document blind image denoiser integrates a Mixture of Experts with a cycle-consistent GAN as the base network that effectively removes multiple types of noise, including salt & pepper noise, blurred and / or faded text, as well as watermarks from documents at various levels of intensity.

Systems and methods are provided for a natural language question answering service to provide answers to natural language questions with respect to network-based services or computing domains. A natural language question answering service may receive a natural language question from a client computing device. An aggregator of a natural language question answer service may retrieve paragraphs from a search system and generate prompts based on questions. A Large Language Model (LLM) of a natural language question answer service may receive cues and provide answers. The answer may be verified by a verifier of the natural language question answering service. Attributes may be applied to answers and retrieved paragraphs to generate references, embedded references, and similar questions. A watermarking module of the natural language question answering service can watermark the answer under the condition that the answer is verified.

The invention relates to a robust watermarking method of a diffusion model based on an error correction code, which belongs to the technical field of large model watermarking, and comprises the following steps of: encoding a watermark message by using a Reed-Solomon error correction code to generate a code word containing redundancy check information; carrying out randomization processing on the code word to generate a pseudo-random bit stream; embedding the pseudo-random bit stream into a variable of an initial Gaussian potential space of a diffusion model by adopting a distribution preserving sampling technology; and finally, generating an image with a watermark through a denoising process of the diffusion model. When the watermark is extracted, reverse diffusion processing is carried out on an image which is possibly damaged to recover an approximate value of a potential space variable, a code word which is possibly damaged is extracted from the approximate value, and original watermark information is recovered by utilizing the error correction capability of a Reed-Solomon decoder. On the premise of keeping the generation performance, the robustness of the watermark to compression, noise, cutting and other potential tampering attacks is enhanced.

A method may include inputting, into a draft model, a sequence of tokens conditioned on a given first context to obtain an original draft distribution of draft tokens. The method may also include applying, based on a watermark code, a reweight function to adjust probabilities of the original draft distribution to generate a watermarked draft distribution of watermarked draft tokens. The method may further include inputting, into a target model, watermarked draft tokens and a sequence of tokens conditioned on a given second context to obtain an original target distribution. In addition, the method may include applying, based on the watermark code, the reweight function to probabilities of the original target distribution to generate a watermarked target distribution of watermarked target tokens. The method may further include sampling a watermarked output from the watermarked draft distribution or the watermarked target distribution based on the adjusted probabilities.

The invention relates to a watermark tracing method and device, electronic equipment and a computer storage medium, and belongs to the technical field of data security, and the watermark tracing method comprises the steps: obtaining the identity feature information of each data receiver and the data feature information of to-be-transmitted source data when a data transmission request of the to-be-transmitted source data is received; adding watermark data in the to-be-transmitted source data based on the identity feature information and the data feature information of each data receiver, and generating to-be-transmitted data corresponding to each data receiver; and when the to-be-transmitted data leaks, leakage tracing is carried out based on the watermark data in the to-be-transmitted data. According to the method, the watermark data is generated by combining the feature information of the data and the identity feature information of different data receivers, the identity features of the data receivers are reserved, meanwhile, the confidentiality of the watermark data is improved, and when the data leaks, the data receivers with data leakage can be determined through the identity feature information in the watermark data.

The invention discloses an image watermarking method and system based on decoding guided by a self-supervised visual model. The method comprises the following steps: acquiring watermark information m and an original image I of each data sample in a training data set; for each data sample, preprocessing the watermark information m to generate a message tensor M, and performing degradation distortion processing on the original image I to generate a distortion guide heat map DGH, thereby obtaining a preprocessed training data set; and performing self-supervising training on the self-supervising visual model by using the preprocessed training data set to finally obtain the trained self-supervising visual model. The invention aims to solve the problem that the decoding robustness is poor when the mask prediction is inaccurate due to the fact that the existing printing-resistant shooting watermark technology excessively depends on the positioning mask, and the semantic comprehension capability of the depth vision model is utilized to replace the traditional geometric synchronization, so that the end-to-end robust decoding without correction is realized.

The invention discloses a secure closed-loop circulation and physical output control method and system for an oversized raster image. The method comprises the following steps: a client adaptively calculates fragmentation granularity according to a network state, fragments an image and encrypts and transmits the image; the server performs secondary encryption and distributed storage on the received data; the preview end constructs a multi-resolution hierarchy based on a viewport mapping technology, only extracts visual slices and superposes watermarks, and transmits the visual slices and the watermarks to a client memory for zero-cache rendering; and the printing end constructs a secure channel bound with a hardware fingerprint, carries out streaming decryption on the data, embeds traceability information, and injects a printing drive in real time. According to the method, the problems of unstable GB-level image transmission and unsmooth preview are solved, and high-efficiency circulation and strict protection of design assets are realized through full-process data non-landing streaming control.

Systems and methods disclosed herein automatically authorize, audit, and manage usage of protected digital content via agentic artificial intelligence (AI) models. A data access / usage request is received (e.g., from a graphical user interface) that is associated with digital assets licensed from third parties. The system uses a first AI agent set to identify the digital content and retrieve corresponding access policies from a distributed database. The system uses a second AI agent set (same as or different from the first AI agent set) to evaluate the request against the retrieved policy to generate a permission set and / or settlement instructions. The system uses a third AI agent set (same as or different from the first and / or second AI agent sets) to embed digital watermarks and / or cryptographic signatures into the accessed content, and to record an audit trail of access, authorization, and / or settlement events in a distributed ledger or database.

The invention provides a credible traceable privacy enhanced heterogeneous federal learning method and system, and belongs to the technical field of artificial intelligence and information security, the method comprises the following steps: initializing a watermark parameter of a pseudo-random code at a server side, and generating a coding key and a decoding key; the client performs coding and tensor remodeling on the message bit sequence of the metadata through the coding key to generate a potential tensor with a watermark; performing reverse diffusion iteration on the potential tensor with the watermark through a pre-trained diffusion model to obtain a generation feature; and the server side performs multi-layer auditing on the client side according to the generation characteristics and the decoding key, and detects whether the client side has malicious behaviors or not. According to the method, the pseudo-random code watermark technology is applied to federated learning for the first time, an unforgeable watermark traceability mechanism is established, malicious behaviors of the client can be effectively monitored, and the method can be widely applied to heterogeneous federated learning scenes.

The invention discloses a watermarking method and device suitable for any resolution image input, and the method comprises the steps: generating a fixed low-resolution watermark residual error through a watermark encoder according to an input carrier image and a watermark message, restoring the watermark residual error to the size of the carrier image, and superposing the watermark residual error with the carrier image to obtain a watermark-containing image; designing a watermark discriminator based on the residual neural network, wherein the watermark discriminator is used for distinguishing the difference between the watermark-containing image and the carrier image; a watermark noise layer is used for simulating various distortion operations suffered by an image under a digital channel, and disturbance is applied to the watermark-containing image processed by a watermark discriminator; and transmitting the watermark-containing image to which the disturbance is applied in a real channel, inputting the watermark-containing image into a robust watermark decoder, and decoding and extracting a watermark message. According to the method and the device, image input of any resolution can be processed, good invisibility and robustness can be kept, and copyright protection and leakage traceability of the image of any resolution can be realized.

The invention provides an automatic evidence obtaining method and device for Internet content, equipment and a storage medium, and the method comprises the steps: obtaining to-be-processed tasks in batches, analyzing the obtained to-be-processed tasks, and obtaining the key task information of each to-be-processed task; based on the task priority and the task type of each to-be-processed task and the resource information of each server node in the server cluster, allocating each to-be-processed task to the corresponding server node; each server node configures a task parameter of a browser instance corresponding to each to-be-processed task based on the task type and evidence obtaining mode of each to-be-processed task to obtain a browser instance adapted to each to-be-processed task; and based on the browser instance adapted to each to-be-processed task, performing loading, screenshot, watermark adding, data packaging and other processing on the target webpage corresponding to each to-be-processed task to obtain an evidence obtaining result of each to-be-processed task. According to the method disclosed by the invention, efficient batch evidence obtaining of the Internet content can be realized.

The invention relates to the technical field of face forgery detection, and particularly provides a face forgery detection method based on watermark feature assistance and cross-task distillation. The method comprises the following steps: constructing a data set of face image samples, and embedding watermarks into the preprocessed face image samples to obtain watermark-embedded images; inputting the watermark-embedded image into the constructed joint training model of watermark extraction and forgery detection double task branches to obtain image fine-grained feature knowledge; knowledge distillation is introduced, image fine-grained feature knowledge is migrated to a counterfeiting detection branch to carry out double-task collaborative optimization, face counterfeiting is detected, and the method improves the detection accuracy.

The application provides a kind of automatic stamping method and system based on invisible watermark, comprising: the electronic text of automatic office unit uploading stamping file and the position information needing stamping;Automatic office unit replaces the electronic text without invisible electronic watermark in process with electronic text;Server informs automatic stamping robot unit to automatically print the electronic text in automatic office unit electronic stamping process;Automatic stamping robot extracts token information in hidden electronic watermark from paper text page by page;If each page token authentication passes, pass through OCR and image matching;Automatic stamping robot stamps information in server through the token of each page text, confirms whether each page text is stamped and where to stamp;Automatic stamping is carried out in the corresponding position of text document, and after stamping is completed, paper document is output.The application can efficiently realize the comparison of paper document and electronic document, and avoid the inconsistency between stamping file and electronic document in approval process.

The invention provides a novel cloud tampering resistant medical image encryption method integrated with a signature watermark, aims to solve the problems of security and integrity of a medical image in cloud transmission and storage and tracing of an image generation source, and designs an improved chirp two-dimensional hyperchaotic system (2D-ICBHM) and an image decomposition encryption method. On the basis of an improved chaotic system, n groups of index scrambling and double chaotic sequence replacement encryption mechanisms are constructed, pixel-by-pixel encryption of the decomposed image is realized, and meanwhile, a block exchange algorithm, a rotation arrangement algorithm and a block diffusion algorithm are designed to complete global block encryption of the image; according to the scheme, a strategy of combining pixel-by-pixel encryption and block encryption is adopted, the encryption effect is ensured under the condition that time overhead is not increased, an integrated doctor signature watermark technology not only realizes verification of an image source, but also can accurately detect a tampering behavior, avoids medical risks, has relatively strong anti-attack and anti-tampering capabilities, and is suitable for large-scale popularization and application. And a promising solution is provided for safe transmission of medical images.

The application relates to the technical field of digital video processing, and discloses a video stream block time evidence watermarking method based on time authentication, which comprises the following steps: receiving a continuous video code stream and dividing the video code stream into multiple continuous video blocks, extracting video coding layer data of the first video block, performing a hash operation to generate a reference hash value; sending the reference hash value to a time watermarking device, performing a digital signature operation on the reference hash value in combination with an absolute timestamp and a signature key to generate a digital signature; intercepting a bit segment from the digital signature as a characteristic sequence to form cascade digest data; and modulating preset macro block syntax elements of the first frame of the next video block by using the cascade digest data, and outputting reconstructed video coding layer data. The method effectively reduces processor occupation and memory consumption of the system, enables video content to meet real-time transmission requirements in a monitoring scene while guaranteeing time sequence and data anti-fake capability.

A system may receive a request to transform predetermined music content using generative artificial intelligence, wherein the predetermined music content is protected by a copyright and is digitally controlled by a cloud-based authorization server. A system may receive a user request to create a derivative work using the generative artificial intelligence, wherein the request includes a prompt from the user to cause the generative artificial intelligence to create the derivative work as a function of the predetermined music content and a user specific theme for the derivative work. A system may model an owner of the copyright with an Al model and approve creation of the derivative work in response to the modeling predicting that the owner would approve the request. A system may create the derivative work using the generative artificial intelligence and may mark the work with a digital watermark for tracking use of the derivative work.

This application discloses a proactive defense method and system based on a large model, relating to the field of security protection technology. The method includes: intercepting malicious requests from external attackers and cleaning sensitive information and adversarial samples from the malicious requests to output standardized data; injecting the standardized data as training data into training adversarial samples to optimize the protection model and ensuring the traceability of the protection model by embedding digital watermarks; deploying honeypot interfaces to lure attackers and trigger countermeasures; generating dynamic defense rules using the protection model; and updating the training adversarial samples in real time for continuous optimization of the protection model. By intercepting and cleaning malicious requests and using honeypot luring and countermeasures, proactive attack detection and early blocking are achieved. Combined with dynamic defense rule generation and continuous optimization of the protection model to adapt to attack iterations, along with a digital watermark traceability mechanism, a closed-loop full-link of "interception-protection-optimization" is constructed, improving the security defense capability of the protection model.