1987 results about "Watermark" patented technology

A network mapping behavior anomaly detection method and system based on machine learning is provided. The method includes: collecting dual-source traffic data, generating a structured log data set through dual-source log fusion engine; performing subgraph matching calculation to obtain a mapping behavior deviation degree; generating communication data containing a watermark identifier in a session corresponding communication path; verifying whether attack events carry the watermark identifier; generating a network mapping behavior anomaly detection report. According to the disclosure, an adaptive attack behavior model is constructed through a multi-modal feature vector based on structured logs and a graph protocol mapping rule base, so that the cognitive robustness to protocol camouflage and path drift is fundamentally enhanced, a real-time verification chain of detection results is built, and traditional passive detection is transformed into self-proof active defense through cross verification of watermark carrying state and behavior trajectory.

Systems and methods are provided for a natural language question answering service to provide answers to natural language questions regarding network-based services or computing domains. The natural language question answering service may receive the natural language question from a customer computing device. An aggregator of the natural language question answering service can retrieve passages from search systems based on the question and generate a prompt. A large language model (LLM) of the natural language question answering service may receive the prompt and provide an answer. The answer may be verified by a verifier of the natural language question answering service. Attribution may be applied to the answers and retrieved passages to produce references, inline citations, and similar questions. A watermarking module of the natural language question answering service may watermark the answer if it is verified.

Herein disclosed is receiving predetermined content, receiving a request to transform the predetermined content into a derivative work, receiving a requested theme for the derivative work, using generative artificial intelligence to create the derivative work generated as a function of the predetermined content and the requested theme, determining if the generated derivative work is approved based on a machine learning model configured to determine a content approval score as a function of content owner preferences, in response to determining the generated derivative work is approved, applying a digital watermark to the approved derivative work, configuring an authorization server to govern use of the approved derivative work based on the digital watermark and providing user access to the authorized derivative work. The requested theme may be determined using a Large Language Model (LLM) and a chatbot interview. The generative artificial intelligence may comprise a diffusion model. The content may comprise music.

Systems and methods are provided for a natural language question answering service to provide answers to natural language questions regarding network-based services or computing domains. The natural language question answering service may receive the natural language question from a customer computing device. An aggregator of the natural language question answering service can retrieve passages from search systems based on the question and generate a prompt. A large language model (LLM) of the natural language question answering service may receive the prompt and provide an answer. The answer may be verified by a verifier of the natural language question answering service. Attribution may be applied to the answers and retrieved passages to produce references, inline citations, and similar questions. A watermarking module of the natural language question answering service may watermark the answer if it is verified.

The invention relates to a security protection method, system and device for data sharing and exchange and a medium. The method comprises the steps that original data are loaded, sensitive information in the loaded data is recognized, and the original data are classified according to the category of the sensitive information; obtaining user demand information and a corresponding target scene condition, adding noise to the sensitive information through a differential privacy algorithm according to the user demand information and the target scene condition, and generating privacy protection data; transmitting and encrypting the privacy protection data to obtain corresponding encrypted data, transmitting the encrypted data through a corresponding encrypted channel, recording an operation log in a data transmission process, and embedding an invisible watermark to track the use condition of the encrypted data; and analyzing the privacy protection requirement of the target scene condition, dynamically adjusting the privacy protection parameter of the encrypted data according to a preset use specification, and recovering the encrypted data when the life cycle of the encrypted data is ended. The method and the device have the effect of improving the data sharing security.

The invention discloses a financial data privacy protection system based on block chain security multi-party computing, and belongs to the technical field of data protection, and the system specifically comprises the steps that a data preprocessing module segments original financial data, and adds a unique watermark identifier; the distributed account book stores the Hash abstract and watermark mapping relation of the encrypted logic data fragment, and the digital signature and the timestamp are fused to ensure reliability; the computing node cluster receives data through a special interface, dynamically builds a computing group according to a service rule and outputs an encrypted computing result; bidirectional authentication is carried out on the zero-knowledge proof verifier and the computing node cluster to verify the data holding right; the encryption proxy gateway processes an output result of the computing node cluster to complete format conversion and ciphertext superposition; the cross-link routing module constructs a virtual coverage layer, cross-link transmission of encryption results is achieved through protocol conversion and three-way handshake verification, and a heterogeneous chain protocol converter and a verification assembly guarantee transmission safety; the financial data privacy security is comprehensively guaranteed, and the data processing efficiency and reliability are improved.

A method is provided for dynamically generating a digital watermark for a data file. The method includes receiving a request to access the data file from a user; dynamically generating an encryption key based on at least one parameter selected from the group consisting of the identity of the user, the time of access, and the mode of access; embedding a digital watermark into the data file using the dynamically generated encryption key, wherein the digital watermark is unique to the request; providing access to the data file with the embedded digital watermark to the user; and storing information related to the encryption key and the parameters used for its generation in a secure database.

Systems and methods are provided for a natural language question answering service to provide answers to natural language questions regarding network-based services or computing domains. The natural language question answering service may receive the natural language question from a customer computing device. An aggregator of the natural language question answering service can retrieve passages from search systems based on the question and generate a prompt. A large language model (LLM) of the natural language question answering service may receive the prompt and provide an answer. The answer may be verified by a verifier of the natural language question answering service. Attribution may be applied to the answers and retrieved passages to produce references, inline citations, and similar questions. A watermarking module of the natural language question answering service may watermark the answer if it is verified.

The invention discloses a cross-border data flow management and control system and method based on privacy calculation verification and a medium. The system comprises a legal knowledge graph construction module, a compliance strategy dynamic generation module, a privacy calculation sandbox module, a data flow topology analysis module and a full-link audit tracing module. Natural language terms are converted into programmable compliance rules through a legal knowledge graph, a technical system is driven to automatically adapt to policy changes, the whole process from single-point protection to full-link privacy calculation is achieved, namely, the whole process of data encryption transmission, secret state calculation and compliance verification is covered, global laws and regulations can be analyzed in real time, and an executable technical strategy can be generated; from sovereign confrontation to sovereign collaboration, a sovereign compliance map is constructed through digital twinning, and a data flow path is optimized. According to the method, digital watermark marking is carried out on all nodes of data flow, traceability and responsibility definition of leakage events can be realized, and a cross-border data flow space-time barrier is broken through.

The invention discloses an enterprise registration archive sharing and shareholder right-of-knowledge guarantee system based on full-chain data tracing and auditing, and relates to the technical field of archive management. The system comprises an identity authentication module, an archive storage management module, an archive sharing module, a shareholder right of knowledge guarantee module, a comprehensive statistics module and a system security module. According to the system, full-chain tracing of archive data is realized by utilizing a block chain technology, all change operations are completely recorded, and the transparency of archive management is remarkably improved; the security and authenticity of the shared archive are ensured through electronic signature, watermark and two-dimensional code anti-counterfeiting technologies; shareholders can track stock equity states and change records of enterprises in real time and know enterprise change information in time through a dynamic notification mechanism, so that the right of knowing of the shareholders is comprehensively guaranteed; through dynamic encryption, authority management and abnormal behavior detection, the security of file storage and access is ensured, and data leakage and tampering are effectively prevented.

Herein disclosed is receiving predetermined content, receiving a request to transform the predetermined content into a derivative work, receiving a requested theme for the derivative work, using generative artificial intelligence to create the derivative work generated as a function of the predetermined content and the requested theme, determining if the generated derivative work is approved, in response to determining the generated derivative work is approved, applying a digital watermark to the approved derivative work, configuring an authorization server to govern use of the approved derivative work based on the digital watermark and providing user access to the authorized derivative work. The requested theme may be determined using a Large Language Model (LLM) and a chatbot interview. The generative artificial intelligence may comprise a diffusion model. The content may comprise music.

The invention provides a block chain-based large model use traceability and access control method and system, and belongs to the technical field of block chains, and the method comprises the steps: extracting key version information of a large model, encrypting the key version information, storing the encrypted key version information to a block chain network, and generating a model evidence storage record; generating a dynamic watermark identifier based on the user identity identifier, the calling timestamp and the model evidence storage record, and embedding the dynamic watermark identifier into an output result of the large model; monitoring calling behavior data of the large model in real time through an intelligent contract in the block chain network; and when abnormal calling behavior data is detected, tracing the source of the abnormal calling behavior data based on the dynamic watermark identifier and the model evidence storage record, and executing permission limiting operation through the smart contract. According to the method, full life cycle protection and calling traceability management of the large model are realized based on the block chain evidence storage, the dynamic watermark identifier and the intelligent contract, so that effective traceability management and access control are realized in the use process of the current large model.

A system and method for implementing multilayer security in documents using multiple codebooks. The system encodes different sections of a document using codebooks associated with specific security clearance levels. Users can only access sections of the document for which they have appropriate clearance, with unauthorized sections appearing redacted. The system provides granular, section-level security while also offering data compression benefits. Additional features include dynamic reclassification, hierarchical codebooks, expiring access, multi-factor authentication, and user-specific watermarking.

The invention provides a cross-platform education data privacy protection analysis system, and relates to the technical field of data privacy protection. The cross-platform education data privacy protection analysis system comprises a multi-modal data acquisition unit, a dynamic privacy analysis engine, a federal learning processing core module, a block chain enhanced access control system, a privacy watermark traceability module and a compliance autonomy unit. Dynamic coupling of scene sensitivity and data protection intensity is realized through a dynamic privacy risk scoring equation and an adaptive differential privacy noise equation; the problems of privacy disclosure, compliance verification and traceability and responsibility investigation in cross-platform education data sharing are solved by combining federal learning, block chain evidence storage and privacy watermarking technologies. According to the method, the privacy risk assessment precision is remarkably improved, the model precision loss is reduced, full-life-cycle data security management and control are supported, and the method is suitable for multiple scenes such as K12 education and college educational administration.

An Automated AI-Driven Lifestyle Orchestration System proactively manages a user's daily life by intelligently populating calendars with relevant, time-sensitive marketing objects. This is achieved through sophisticated AI-driven analysis of user directives, preferences, and real-time location data obtained via computing devices like smartphones. The system leverages advanced media identification modules employing fingerprinting and watermarking to accurately match user-captured media (via a Percipient Sample Pack (PSP)) to specific content and associated products. It facilitates dynamic commerce through hierarchical linked lists for purchasing authentic or similar items, supported by an affiliate program. This inventive solution significantly improves personal organization and digital commerce by transforming passive interaction into a proactive, intelligent, and monetizable user experience.

The invention provides a security risk detection method and device for text graph large model generation content, and the method comprises the steps: selecting a test category according to a test parameter based on a preset test database, and matching a corresponding data set from the test database according to the test category; inputting the keywords in the data set into the tested large model in batches according to the format of forward cue words; performing content security detection on a corresponding picture or video image generated by the detected large model according to the input cue word; performing watermark identification detection on a corresponding picture or video image generated by the detected large model according to the input cue word; and analyzing to obtain a detection report according to the content security detection result and the watermark identification detection result. According to the test database, the risk of the large model system is externally assessed based on the characteristics of the input prompt word, the content annotation and the output video content, and the accuracy and effectiveness of the detection and assessment method are improved.

The invention discloses an industry return on investment real-time acquisition method based on multi-source heterogeneous data, and relates to the technical field of data analysis and processing, and the method comprises the following steps: normalizing a multi-source timestamp and retaining metadata information based on a UTC reference, an adjustable gain and a power exponent; in the streaming processing, reordering of out-of-order data and marking of expired data are realized by setting a buffer queue and a watermark threshold value; when null value fields or cross-source conflicts are detected, interpolation and conflict processing are carried out, and complete data subjected to consistency correction are output; then, an external high-precision reference or a cross-correlation function is used for further fine tuning the timestamp at a millisecond level, and if the adjustment amplitude exceeds a safety boundary, the timestamp is marked as suspicious; and finally, the corrected data is distributed to multiple nodes according to a fragment mapping strategy, and fault-tolerant consensus and difference repair are triggered under fault duration judgment, so that high-precision time sequence alignment and high availability in a massive concurrent scene are kept, data loss or precision attenuation caused by time sequence inconsistency and node faults is avoided, and the method can be widely applied to high-frequency analysis.

Provided herein are systems, methods, computer-readable media, and techniques for providing trusted artificial intelligence (AI) using Fully Homomorphic Encryption (FHE), comprising: (A) providing a deep neural network (DNN)-based model with modified architecture, wherein the modified architecture at least (i) uses a Gaussian function as an activation function and (ii) removes one or more pooling layers; (B) obtaining encrypted data, wherein the encrypted data are generated by applying the FHE to plaintext data; and (C) generating an inference with the DNN-based model based on the encrypted data. Further provided herein are systems, methods, computer-readable media, and techniques for providing trusted AI using stochastic computing, using noise based computing, using an artificial immune system, and with secure multi-party computation (SMPC) based at least in part on watermarking.

The invention relates to the technical field of Internet of Things data transmission, in particular to a mass data cross-security domain transmission high-low priority queue hierarchical scheduling method based on Internet of Things equipment, which comprises edge computing node classification, independent channel design, a dynamic weight distribution algorithm and a block chain encryption watermark technology. The timeliness is improved through a preemptive and compensation mechanism, and the reliability is enhanced in combination with queue degradation protection and a dynamic adjustment strategy. The method can effectively solve the problems that timeliness is insufficient and safety and efficiency are difficult to balance in a traditional method, the key data transmission efficiency and the system self-adaptive capacity are remarkably improved in a complex network environment, and the method has wide application prospects.

The invention discloses a short video production method and system based on artificial intelligence, and relates to the technical field of multimedia processing, and the method comprises the steps: inputting a split script into a multi-modal generation engine, employing a lower triangle space-time attention matrix to generate a visual stream, and generating a text stream and an audio stream; calculating a neural conduction delay amount between the visual stream and the audio stream based on an audio-visual perception delay prediction model, and generating a corrected audio stream through time axis forward compensation; calculating a cross-modal attention weight matrix according to the node association strength of the dynamic causal graph, and projecting the text stream and the corrected audio stream to a joint feature space to generate a multi-modal fusion feature; and inputting the multi-modal fusion features into a format adaptation engine, and after time-space consistency verification, embedding a neural implicit watermark and encoding the neural implicit watermark into a short video. According to the invention, the semantic consistency and coordination among the text, the audio and the visual content are improved, so that high-quality and high-intelligence automatic generation of the short video is realized on the whole.

Disclosed are systems and methods including software processes executed by a server for obtaining, by a computer, an audio signal including synthetic speech, extracting, by the computer, metadata from a watermark of the audio signal by applying a set of keys associated with a plurality of text-to-speech (TTS) services to the audio signal, the metadata indicating an origin of the synthetic speech in the audio signal, and generating, by the computer, based on the extracted metadata, a notification indicating that the audio signal includes the synthetic speech.

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.

A method of controlling access to a digital resource of a group of digital resources, the method comprising: receiving a request from a user via a computer browser of a user equipment for access to a digital resource of a group of digital resources; determining if the resource comprises at least one information sensitive feature; determining for each of the determined at least one information sensitive feature a confidence level (CON) for the feature; determining for the user a clearance level (CLR) for each of the determined at least one information sensitive feature; if the request for access is allowed, determining whether to watermark the resource responsive to the CON and the CLR for each of the at least one information sensitive features; and if it is determined to watermark, watermarking the resource without affecting data defining the resource at a source from which the resource is downloaded to provide the requested access.

The invention belongs to the field of privacy protection data, and provides a privacy protection data exchange method and system under a zero-trust network architecture in order to solve the problem that a traditional scheme cannot cope with the privacy leakage risk through data analysis. The privacy protection data exchange method under the zero-trust network architecture comprises the following steps: performing tagging processing on user behavior data, equipment state data and operation environment data; executing multi-dimensional dynamic risk assessment, and calculating a comprehensive risk score; adjusting privacy budget and noise intensity according to a comprehensive risk scoring result, and protecting a data query result in combination with an adaptive differential privacy mechanism; performing dynamic data desensitization based on information entropy on a data query result; embedding a self-evolved data watermark into the data after the data query result desensitization processing is completed; the embedded watermark data is exchanged through the encrypted transmission channel, and the transmission process is monitored in real time, so that the security and integrity of the data exchange under the zero-trust network architecture are ensured.

The invention discloses a digital reading system based on a knowledge graph and a text image recognition technology. The system comprises a collection module used for collecting financial data and a first financial document from a plurality of financial data sources; the construction module is used for identifying a target entity in the financial field in the financial data and constructing a graph structure of a financial knowledge graph; the first analysis module is used for receiving a second financial document uploaded by the user, identifying a target keyword in the second financial document and generating a mind map corresponding to the target keyword according to a preset hierarchical structure; the second analysis module is used for identifying document elements in the first financial document; the typesetting module is used for acquiring screen information of the mobile terminal equipment; the watermark adding module is used for generating a digital watermark according to the copyright information and the custom information; and the question processing module is used for receiving the query question. The technical problem that financial knowledge processing efficiency of a related digital reading system is low is solved.

Authenticity of a sticker (e.g., a mark-down sticker on a retail item), or integrity of a closure (e.g., on a delivery bag or package), is confirmed by reference to spatial information. In some embodiments a fingerprint is formed from parameters describing spatial placement of a sticker or pattern on a substrate. In some embodiments a digital watermark pattern provides a spatial frame of reference within which one or more other features can be located. In still other embodiments, a package is sealed with a shipping tape marked with a digital watermark. If the tape is slit to tamper with package contents, and is then repaired by an overlay of clear tape, the repair betrays itself by a forensic inspection that reveals a diminution in watermark strength. A great many other features and arrangements are also detailed.

The invention discloses a file fragment encryption transmission method and device based on a B / S architecture, and belongs to the field of information security. The problem of systematic contradiction among file transmission efficiency, safety and reliability is solved. The method comprises the following steps: determining a fragmentation threshold value, and carrying out self-adaptive fragmentation processing on an original file; respectively performing RSA public key encryption and AES random key secondary encryption on each fragment file to generate a double-encrypted file; writing the SHA-3 hash value of each fragment file and the timestamp information into a block chain network to generate a non-tampering meta-file; a multiplexing transmission channel is established, a meta-file and an encrypted file set are downloaded at the same time, and each fragment adopts an independent transmission thread; verifying the consistency of the Hash value of the downloaded file and the blockchain evidence, and executing an exponential backoff retransmission strategy on the fragments which fail in verification; and performing streaming decryption recombination on the verified fragments to generate a temporary file with a digital watermark. The method is mainly used in data transmission field.

Systems and methods are provided for a natural language question answering service to provide answers to natural language questions regarding network-based services or computing domains. The natural language question answering service may receive the natural language question from a customer computing device. An aggregator of the natural language question answering service can retrieve passages from search systems based on the question and generate a prompt. A large language model (LLM) of the natural language question answering service may receive the prompt and provide an answer. The answer may be verified by a verifier of the natural language question answering service. Attribution may be applied to the answers and retrieved passages to produce references, inline citations, and similar questions. A watermarking module of the natural language question answering service may watermark the answer if it is verified.

The invention relates to the technical field of anti-counterfeiting watermarks, in particular to a digital intelligent water affair form text anti-counterfeiting watermark generation method based on an open source gap, which comprises the following steps of: acquiring field difference and repetition frequency, screening jitter fields to generate a perturbation table, indexing and marking sensitive segments in sections, establishing a weight structure and adjusting bit width, and sequencing nodes to generate a binding list. And constructing a watermark path chain, and matching track consistency to generate a drift label. According to the method, a field disturbance weight structure is established through proportional mapping, dynamic affinity sorting is performed in combination with node processing capacity and field task attributes, watermark track sequence binding is realized in a field path structure, and a track consistency detection mechanism is introduced in time sequence matching of field filling and node execution. The concealment of field embedding disturbance and the verifiability of a watermark writing path can be enhanced under the condition of not changing a form external display structure, and it is ensured that node selection in the field content embedding process has logical continuity and a track chain can be traced back.

The invention provides a multi-party data sharing data sandbox and method. The multi-party data sharing data sandbox comprises a preprocessing module, a security access module, a sandbox core module and an output control module, the preprocessing module is used for desensitizing, fragmenting and encrypting original data; the security access module is used for establishing an encrypted transmission channel and executing identity authentication; the sandbox core module is used for executing a cross-domain calculation task, and data are kept in an encrypted state in the calculation process; and the output control module is used for desensitizing a calculation result, embedding an invisible watermark, triggering a multi-party approval process and outputting data after approval is passed. The technical problem that in the prior art, the requirements of data non-landing, multi-party joint governance and dynamic authority control are difficult to meet at the same time can be effectively solved.