21 results about "Internet users" patented technology

The invention discloses an internet user behavior accurate analysis method based on artificial intelligence, which belongs to the technical field of internet and comprises the steps of S1, data acquisition and privacy enhancement processing, S2, behavior modeling and transparent analysis, S3, real-time risk prevention and control and abuse blocking and S4, feedback closed loop and continuous optimization. On the basis of analyzing user behaviors, the traditional contradiction between privacy and efficiency can be broken through, and systematic improvement of safety and efficiency can be achieved.

The invention discloses an Internet user behavior accurate analysis method based on artificial intelligence. The method comprises the following steps: obtaining user behavior data of an Internet platform; inputting the user behavior sequence into a Mamba network to generate a behavior state vector; inputting the commodity image set into an improved DeiT model, and setting a hierarchical feature routing controller; executing cross-modal feature interaction to generate a fusion feature tensor; inputting the fusion feature tensor into an IQL network; updating a fusion weight, high-level attention mapping and a routing control vector based on a value gradient resonance feedback mechanism; and outputting a user behavior analysis result and a personalized recommendation result. According to the method, the accuracy of Internet user behavior prediction and personalized recommendation can be remarkably improved, and the method is suitable for scenes needing high-precision user portraits and intelligent recommendation, such as a large-scale e-commerce platform and a content distribution platform.

To provide an information processing system and method for reducing labor and time when manually monitoring contribution information contributed to a plurality of contribution sites.SOLUTION: In the information processing system, a management server 10 includes an acquisition unit 11 that acquires posted information corresponding to a specific object from each of a plurality of posting sites (posting site servers) that disclose posted information posted by users who have used the specific object on the Internet, and an output unit 12 that outputs the posted information corresponding to the specific object acquired from each of the plurality of posting sites to be displayed in a list.SELECTED DRAWING: Figure 2

This application provides a general online AI streaming processing method, apparatus, device, and medium. The method includes: querying the cached results in the video AI buffer of an AI server based on a video prediction request sent by a user; if no cached result corresponding to the URL address is found in the video AI buffer, the video AI processing thread of the AI ​​server checks whether a playback instruction sent by the user has been received within a preset time threshold from the first current time; if a playback instruction sent by the user is confirmed to have been received, the video AI processing thread retrieves the video image from the media server pointed to by the URL address, and sends the AI ​​prediction result of the video image as the cached result corresponding to the URL address to the video AI buffer. This method allows a wide range of internet users to find different media servers based on different URL addresses and perform online AI prediction on the video images from the media servers, which is very convenient.

The application discloses a DNSKEY smooth change-based authoritative server abnormal change detection method and system, and belongs to the DNS security field. The application is based on the rule that DNSKEY cannot be directly updated along with the change of the authoritative server of a domain name, uses trusted DS records to verify DNSKEY, thereby verifying the authenticity of the change of the authoritative server of the domain name, and accurately identifying the abnormal change of the authoritative server. A DNSKEY smooth change-based authoritative server abnormal change detection system is constructed, can perform timed detection on the domain name, accurately identifies the abnormal change of the authoritative server of the domain name, and avoids the adverse effects of the domain name on internet users after the domain name is maliciously tampered with.

The present application relates to the technical field of artificial intelligence, in particular to a slow internet user identification method, device and equipment and computer storage medium. The slow internet user identification method disclosed by the present application uses the random forest and curve fitting method in machine learning to identify the slow internet user of home broadband. The random forest algorithm is used to determine the importance of the index, the curve fitting is used to determine the index threshold, the slow internet user identification rule is obtained, and the slow internet degree of the user identified as the slow internet user is calculated through the formula, so that the quantitative division of the slow internet user is realized, and the accuracy of the slow internet user identification is improved.

The present application relates to the field of data feedback analysis, and more particularly to an internet new media data feedback generation method and system. The method comprises the following steps: obtaining new media video in production and internet user feedback big data; performing multi-period decomposition and individual video segment deep semantic analysis on the new media video to construct multiple content label video segments; performing social communication effect mining and video communication effect conversion rate calculation according to the internet user feedback big data to generate the social communication conversion rate of each video segment; performing positive and negative communication effect inference according to the social communication conversion rate, and performing communication conversion value evaluation on the multiple content label video segments to generate the communication conversion value of each video segment. The present application dynamically optimizes new media data based on user demand and interest feedback, and extracts the quality and communication effect of video content.

Techniques for anonymizing user activity. Messages from a C3N user device may be processed by a proxy application running within a containerized environment of the device. Messages may be directed to a C3N grid network for endpoints located within the C3N ecosystem and avoid the Internet entirely. User activity can be obfuscated by nodes of the grid network, which can generate and / or route fake messages along with a real message.

Methods and systems for identifying potentially harmful misdirection to a malicious URL to thwart a malicious phishing attack. The methods and systems capture an image of a target URL of a high-risk website and analyze the captured image to compare the apparent meaning of the captured image to a set of known URLs. Differences between the captured image and the known URLs are calculated based on a zone of familiarity for an Internet user calculated on prior computer activity of the user and a departure of the target URL from the zone of familiarity. The method and system identify whether the target URL is a potentially malicious URL based on the calculated difference. A warning is generated if the target URL is identified as a potentially malicious URL.

An exemplary system and method for employing (i) a private spectrum bastion configured to verify every request to access a public server and respond to the requests with puzzles having spectrum access information to limit the impact of malicious traffic to a network spectrum, and (ii) privacy-preserving transmission and authentication protocols that obfuscate internet users' identifications when they request access from or communicate with a public server. The bastion provides computational puzzles embedded with spectrum access information to throttle malicious traffic at the network spectrum. The bastion operates with post-quantum cryptographic components and privacy-preserving protocols. The privacy-preserving protocols remain confidentiality of user identities and access patterns.

The invention provides a quasi-real-time dynamic IP blacklist control method, a storage medium and electronic equipment. The method comprises the following steps: collecting log data accessed by Internet users based on a distributed message queue; acquiring user access feature data for the log data accessed by the internet user based on a real-time analysis database; judging whether an abnormal IP identification process is triggered based on the user access feature data, performing abnormal IP risk assessment based on the user access feature data, a plurality of preset abnormal IP matching factors and a priority sequence of the matching factors when the abnormal IP identification process is triggered, and determining a blacklist IP list according to a result of the abnormal IP risk assessment; and synchronizing the blacklist IP list to a cache service, and intercepting the IP in the blacklist IP list based on interaction between a web service and the cache service. According to the invention, the real-time performance and accuracy of IP blacklist protection can be effectively improved.

This invention belongs to the field of internet user preference prediction technology, specifically relating to a user preference prediction method based on data debiasing. The method includes: acquiring video data and user data; processing the video data and user data using an embedding layer to obtain user embeddings and video embeddings; debiasing the user embeddings and video embeddings to obtain debiased user embeddings and debiased video embeddings; processing the user embeddings, video embeddings, debiased user embeddings, and debiased video embeddings using a feature filtering layer to obtain user-specific feature importance weights and video-specific feature importance weights; processing the user-specific feature importance weights and video-specific feature importance weights using a factorization machine to obtain a user interest representation vector; and inputting the user interest representation vector into an output layer for processing to obtain the user preference prediction result. This invention can accurately and effectively predict user preferences, improving the accuracy of user preference prediction.

This invention discloses an intranet traversal system, comprising a client and a server. The client runs on a computer within a local area network (LAN), and the server runs on a cloud host. Each client connects to an internal service within the LAN. When the corresponding internal service requires traversal, the client initiates a connection request to the server. The server receives the connection request from the client, establishes a tunnel with the client, and starts a proxy service for the internal service corresponding to that client. The proxy service receives access requests from internet users and forwards them to the internal service within the LAN via the server and client. This invention provides strong computing and storage services while controlling costs and simplifying intranet traversal operations.

This invention belongs to the field of internet user access experience technology, specifically relating to an internet access quality monitoring system and method for real-time perception of user experience. This invention constructs a diffusion intensity index by using the adjacency matrix change rate and the experience quality index change rate. This index can identify whether network quality anomalies are propagating in the spatial structure, achieving an improvement from single-point anomaly monitoring to group trend monitoring. The network performance sampling frequency is dynamically adjusted according to the diffusion intensity, improving sampling accuracy during anomaly propagation and reducing sampling load in stable conditions. This reduces system resource consumption while ensuring monitoring accuracy. By integrating individual network performance, spatial adjacency relationships, time window fluctuation statistics, and diffusion trend judgment, real-time dynamic perception and adaptive monitoring and control of user experience quality are achieved, resulting in significant improvements in anomaly identification accuracy, group diffusion perception capability, and system resource utilization efficiency.

A method and system for authenticating an Internet user identity by cross-referencing and comparing at least two independent sources of information. A first geographical location of computer signature of an internet user is identified and the geographical location of a communication voice device of said internet user is identified to determine a second location. The first and second locations are compared for geographical proximity to confirm the identity of the internet user. Based upon geographical proximity of said locations, a score is assigned to the internet user, and access to a website is allowed or limited based upon said score. Alternatively, additional authentication information can be required or access can be terminated.

A method for authenticating the identity of a user who is attempting to access a website or conduct a transaction is described. The method involves receiving two geographical locations, and associated time stamps, of a mobile phone associated with the user, one of the locations being the location of the transaction or access attempt. The method determines whether the speed required to travel between the two geographical locations in the elapsed time is within acceptable limits. A confidence score, derived in part from this calculation, is taken into account when deciding whether to allow or deny the access or the transaction.

The invention discloses a cross-network mobile office security method, which comprises the following steps that: an internet mobile office terminal performs identity authentication on an internet user, performs terminal identity authentication, performs security detection and reinforcement on a mobile terminal, and starts local security control measures of the internet terminal for mobile office. An encryption network transmission channel based on the national commercial password technology is established, and a mobile office sentinel system deployed on the Internet side is accessed. The method has the significance and value that the content of the remote mobile application is richer and can cover all service applications and data allowed by the Internet and the non-secret-related private network; the remote mobile application is safer; loose coupling is easy to integrate. According to the invention, technologies of zero trust, password, cloud computing, artificial intelligence and the like are comprehensively utilized, existing security construction achievements of the Internet and a non-secret-involved private network are reused, and the method focuses on a security channel and a WEB remote office platform of mobile office.

Watermarking media content, in combination with blockchain and distributed storage networks, prevents the proliferation of Deepfake content. Digital watermarks are embedded in the audio and video tracks of video clips of trusted content producers at the time the videos are captured or before they are distributed. The watermarks are detected at the social media network's portals, nodes, and back ends. The embedded watermark imparts a unique identifier to the video, that links it to a blockchain. The watermarks also allow video source tracking, integrity verification, and alteration localization. The watermark detectors can be standalone software applications, or they can be integrated with other applications. They are used to perform three main tasks: (1) they alert the Internet user when he watches an inauthentic news video, so that he may discard it, (2) they prevent a Deepfake content from propagating through the network (3) they perform forensic analysis to help track and remove Deepfake content postings.

Watermarking media content, in combination with blockchain and distributed storage networks, prevents the proliferation of Deepfake content. Digital watermarks are embedded in the audio and video tracks of video clips of trusted content producers at the time the videos are captured or before they are distributed. The watermarks are detected at the social media network's portals, nodes, and back ends. The embedded watermark imparts a unique identifier to the video, that links it to a blockchain. The watermarks also allow video source tracking, integrity verification, and alteration localization. The watermark detectors can be standalone software applications, or they can be integrated with other applications. They are used to perform three main tasks: (1) they alert the Internet user when he watches an inauthentic news video, so that he may discard it, (2) they prevent a Deepfake content from propagating through the network (3) they perform forensic analysis to help track and remove Deepfake content postings.

The present application relates to the technical field of data analysis, and particularly relates to an internet user portrait generation method based on big data, which comprises the following steps: obtaining the search times and search depth of a target data type obtained by browsing a webpage in a user monitoring time period, obtaining the search progression performance of the target data type, combining the interlaced search condition of other data types in the search process of the target data type, and obtaining the browsing concentration degree of the target data type; obtaining the increase degree of the browsing concentration degree based on the change trend of the browsing concentration degree of the target data type in multiple continuous monitoring time periods; and according to the increase degree of the browsing concentration degree, combining the browsing concentration degree of the target data type and the latest search time interval of the target data type, correctly mining the portrait importance degree of each target data type of the user, and improving the accuracy of the user portrait when performing the portrait of the user according to the portrait importance degree of each target data type.

This invention relates to a method for predicting internet user ad clicks based on big data, belonging to the field of internet advertising technology. It aims to solve the problems of difficulty in modeling high-dimensional sparse features, insufficient capture of feature interactions, and weak prediction generalization ability in existing technologies. The method first acquires user features, ad features, and historical behavior sequences. User and ad features are divided into coarse-grained and fine-grained categories and encoded. Low-dimensional dense features are extracted through feature processing. Next, the user's historical behavior sequences are embedded and sequence modeled to obtain dynamic interest vectors. Subsequently, the dynamic interest vectors are concatenated with the coarse-grained low-dimensional features, and dynamic sample clusters are obtained through clustering. A dedicated model is built for each cluster, fusing fine-grained features. Finally, the fused features are input into a deep neural network containing both click and deep interaction tasks, outputting the prediction results. This invention, through layered processing of coarse and fine-grained features, clustering and grouping modeling, and dual-task collaborative optimization, effectively mines deep feature correlations, accurately captures user dynamic interests, and significantly improves the accuracy and generalization ability of click prediction, providing reliable support for precise ad targeting.