167 results about "Digital watermarking" 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 is suitable for the field of digital watermarking, and provides an anti-compression coding robust video watermark generation method based on an adversarial neural network, and the method comprises the steps: constructing an MSCA-GAN model; the model comprises an encoder, a decoder, a distortion layer, a discriminator network and an opponent network, and the specific steps are as follows: step S1, the encoder extracts different scale features of a video frame by using a multi-scale convolution attention mechanism, calculates attention weights, efficiently hides and embeds binary watermark information into the video, generates a watermark-containing video, and transmits the watermark-containing video to the decoder; performing confrontation optimization on an embedding strategy with a discriminator in training; according to the method, for H.264 compression layer special training, the multi-scale convolution attention mechanism and the depth separable convolution are combined, and the anti-compression robustness of the watermark under the H.264 standard is effectively improved; through common attack training such as noise layer simulation cutting and zooming, the watermark can still keep high extraction accuracy and robustness in a complex environment.

The invention provides an AI knowledge base construction method and system for multi-source data integration, and belongs to the technical field of knowledge base construction. The method comprises the following steps: adaptively pulling unstructured data at an API-free site through a reversible crawler of a heterogeneous data access framework; the mode drift detector senses field change in real time and updates a protocol in a hot plug mode within 500ms, so that zero-stop synchronization is realized; carrying out weighted resolution on conflicts according to source credibility index attenuation, and generating version stamps with digital watermarks and consanguinity URI (Uniform Resource Identifier) for records; uniformly mapping to a shared semantic space through cross-modal comparative learning, and constructing an incremental hypergraph knowledge graph which can be evolved by probability weight; and extracting an optimal sub-graph by using generative adversarial reinforcement learning, writing the optimal sub-graph into a time sequence knowledge warehouse by using a zero knowledge evidence chain and carrying out block chain solidification, and outputting a verifiable certificate. By the adoption of the AI knowledge base construction method and system for multi-source data integration, end-to-end automatic, high-credibility and traceable large-scale knowledge base construction is achieved.

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 provides a watermark processing method and device, watermark processing equipment, a program product and a medium, and relates to the technical field of privacy computing. The method comprises the following steps: acquiring first data which is requested to be input into a target model by a user through an application programming interface (API); aiming at the first data, judging whether watermarking processing needs to be carried out or not; when it is determined that watermark processing needs to be carried out, based on a backdoor function corresponding to the target model, an API response corresponding to the API request is generated according to the first data, and the backdoor function is constructed according to a decision function of the target model; the API response is output to the user, the first data is added to a trigger set corresponding to the target model, and the trigger set is used for verifying an alternative model of the target model. According to the scheme of the invention, the problem that the existing digital watermarking technology is difficult to effectively defend model extraction attacks initiated through an API (Application Program Interface) is solved.

The invention discloses a statistical data downloading method for supply chain finance, which relates to the technical field of finance and comprises an acceptance permission judgment module, a query resource control module and a desensitization packaging evidence storage module. The acceptance permission judgment module is used for uniformly accessing the statistical application, completing identity verification, main body range binding, index range binding, time range binding and area range binding, and generating an acceptance bill and a judgment bill; the query resource control module is used for generating a query plan under the index aperture mapping dictionary, the partition information and the resource quota, binding a concurrent quota, a throttling quota and a priority queue, and outputting an executable instruction stream; and the desensitization packaging evidence storage module is used for executing differential desensitization according to the main body type and the sensitivity level, performing aggregation calculation and deduplication execution, completing result set packaging, digital watermarking and downloading delivery, generating a downloading certificate and writing a certificate abstract and an evidence index into an evidence storage chain. The method has the characteristic of high consistency.

Systems, methods and technology for authenticating multi-layered objects using encoded signals such as digital watermarking. In one implementation, a value document includes a substrate and a removable overlayer, with a security feature comprising a digital watermark signal printed to cover portions of both the substrate and overlayer. The digital watermark signal includes spatially arranged signal elements forming a frame of reference. Tampering is detected by evaluating offset values associated with the signal elements, where misalignment within the frame of reference indicates tampering. In some implementations, the value document includes a first digital watermark on the substrate with synchronization and payload components, a token with a second digital watermark, and a removable sticker with a third digital watermark. Additional security features include split-mark configurations, tamper mark configurations, holographic foils with overprinted digital watermarks, and fragile tamper-deterrent features that deform upon tampering attempts, causing detectable signal distortion. Other combinations are also provided.

The invention discloses an attacker tracing method, device, equipment, medium and product in a network security penetration test, and the method comprises the steps: firstly building a session connection between a client and a target system when the penetration test is started; after the session is established, the client synchronously creates a unique traceability identifier when generating an attack load, and embeds the unique traceability identifier as a digital watermark into the attack load to form load watermark data; constructing a network data packet based on the data and sending the network data packet to a target system through a session channel; carrying out distributed credible storage on attack behavior logs generated in the penetration process by adopting a preset consensus mechanism; after the test is finished, the stored log data is automatically aggregated, an electronic evidence packet meeting judicial requirements is generated, and the whole penetration test process is completely recorded, the technical scheme of the embodiment of the invention can effectively prevent the denial behavior of an attacker, ensure the traceability of the penetration test process, and significantly improve the credibility and legal potency of evidence collection after the event.

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 multi-medical image encryption method with tampering localization capability, and aims to solve the problems of security and integrity of digital medical images in transmission and storage, and the core is to provide localized tampering prevention capability. According to the method, firstly, a novel two-dimensional S-type logarithmic chaotic mapping 2D-SLCM is utilized to generate a secret key and a chaotic sequence which are highly related to plaintext content so as to resist differential attacks; then, performing efficient compression on each medical image by adopting a block compressed sensing (BCS) technology to ensure the transmission efficiency; in the encryption stage, data confidentiality is ensured through a multi-layer encryption process including local binary tree traversal scrambling and global random block scrambling; most importantly, an encrypted unique digital watermark is embedded into each image before the images are merged; the dual mechanism not only can detect the tampering behavior, but also can accurately identify which image in the multi-image set is damaged by verifying the watermark extracted from each image, thereby ensuring the reliability of residual data.

The invention discloses an anti-printing and anti-scanning digital watermark method for a text image, which comprises the following steps of: embedding and extracting a watermark on the basis of a stroke-like thought, segmenting characters and determining the average skeleton quality ASM of each character during embedding, and forming a group by every two characters, changing the ASM of each group of characters according to the to-be-embedded information to embed the watermark and replace the corresponding characters of the source document; during extraction, two characters are also taken as a group, ASM is extracted, and watermark information is extracted by comparing ASM among the characters, so that 1-bit information can be embedded into the two characters, the language type and font of the characters are not limited, the watermark information amount of the document is ensured, and meanwhile, the watermark information is extracted. The problems that algorithms among different languages are limited, and the robustness is poor and the capacity is small when digital watermarks in a space domain and a transform domain resist printing and scanning attacks are effectively solved.

A method in an illustrative embodiment includes generating structured noise of first synthesized audio based on the first synthesized audio, and fusing a digital watermark into the structured noise. The method further includes determining a target embedding position of the digital watermark based on a spectrum of the first synthesized audio, wherein the digital watermark indicates a source of the first synthesized audio. In addition, the method further includes generating second synthesized audio based on the fused structured noise, the first synthesized audio, and the target embedding position. Through the method, not only is content of original audio preserved, but also a watermark is added, allowing a source of the audio to be recorded and traced. At the same time, the method further has a high degree of covertness, robustness, and flexibility, thereby providing a safer and more reliable environment for the synthesized audio, and improving the user experience.

The invention provides a video processing method which can be applied to the technical field of audio and video. The video processing method comprises the following steps: acquiring a currency counting video, a currency identification and transaction information of a currency counting machine, wherein the transaction information represents information associated with currency counting; converting the transaction information into a digital watermark, and embedding the digital watermark into the currency counting video; adding a banknote identifier to the embedded banknote counting video to obtain an additional video; based on the content complexity of the additional video, slicing the additional video to obtain a plurality of video clips; and compressing the plurality of video clips to obtain a target video which is used for verifying the source uniqueness of the currency counting video. The invention further provides a video processing device, equipment, a storage medium and a program product.

A waste stream is analyzed and sorted to segregate different items for recycling. Certain features of the technology improve the accuracy with which waste stream items are diverted to collection repositories. Other features concern adaptation of neural networks in accordance with context information sensed from the waste. Still other features serve to automate and simplify maintenance of machine vision systems used in waste sorting. Yet other aspects of the technology concern marking 2D machine readable code data on items having complex surfaces (e.g., food containers with integral ribbing for structural strength or juice pooling), to mitigate issues that such surfaces can introduce in code reading. Still other aspects of the technology concern prioritizing certain blocks of conveyor belt imagery for analysis. Yet other aspects of the technology concern joint use of near infrared spectroscopy, artificial intelligence, digital watermarking, and / or other techniques, for waste sorting. A variety of further features and arrangements are also detailed.

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.

The invention provides a knowledge asset traceability tracking method based on digital watermarking, and the method comprises the steps: obtaining to-be-protected knowledge assets, and extracting the multi-modal feature representation of the knowledge assets; according to the method, spatial intensity mapping is dynamically generated by combining a prediction model, intelligent embedding is realized, a DWT-SVD mixed domain core technology is adopted, the multi-resolution analysis capability of discrete wavelet transform and algebraic stability of singular value decomposition are fully played, tracing anchor points are provided for watermarks, and meanwhile, a multiple security guarantee system is constructed, so that the security of the watermarks is improved. And finally, an asset identification module, a watermark generation module, an intelligent embedding module, a traceability verification module and an audit report module are integrated through end-to-end systematic design, so that a complete management closed loop is formed, and the system universality is improved. The full-life-cycle management function enables intellectual property risk management and control through log auditing and a visual report, so that the concealment and safety of the digital watermark are improved.

The invention relates to the field of artificial intelligence medical treatment, in particular to a self-adaptive health care robot interaction method, which comprises the following steps of: acquiring facial tongue pictures, physiological waveforms, body fluid chemistry and environmental behavior information, encrypting fragments, writing a hash chain and embedding a digital watermark; after decryption, quantizing the signal into a pulse sequence, inputting the pulse sequence into a liquid state machine to generate a pulse grid, extracting a topological signature, cascading the topological signature with a multi-scale feature, and obtaining a digital twin state vector through a streaming variational encoder; the vector is mapped to a directed acyclic causal diagram, fractional order diffusion is applied to form a propagation tensor, an Isin model is constructed, minimum energy spinning is obtained through silicon optical coherent annealing, and an intervention effect vector is generated through write-back simulation; taking the digital twin state and the intervention effect as input, and adopting an energy covariance constraint near-end strategy to optimize an output care plan; if the confidence is insufficient or drug conflicts are detected, manual confirmation is triggered; according to the invention, low-delay, interpretable and end-to-end encrypted family health closed-loop intervention is realized.

This invention discloses a method and system for generating digital watermarked images. The method includes: acquiring an original image to be watermarked; generating an image coding mask based on the image complexity of the original image; performing frequency domain decomposition on the original image to obtain a low-frequency component image; embedding an initial watermark image into the low-frequency component image according to the embedding strength values ​​corresponding to the masks in the image coding mask to obtain a low-frequency watermark image; different masks in the image coding mask correspond to different embedding strength values; and performing an inverse frequency domain transform on the low-frequency watermark image to obtain a synthesized watermark image. This invention can improve the success rate and accuracy of watermark extraction.

Systems, methods, and apparatuses are described herein for obtaining an image, wherein the image includes a digital watermark that embeds metadata associated with at least one object in the image, and wherein the metadata comprises an indication of a location of the at least one object in the image. The embedded metadata may be extracted based on the digital watermark. Based on the extracted metadata, a portion of the image corresponding to the location of the at least one object in the image may be caused to be selectable to access supplemental information related to the at least one object.

A visual media is received. For example, the received visual media may be a digital image, a video file, or a video stream. A plurality of colors in the visual media are identified. In response to identifying the plurality of colors in the visual media, one or more colors not in the visual media are identified. A watermark is placed in the visual media to produce a watermarked visual media. The watermark comprises at least one of the identified colors not in the visual media. The watermarked visual media is verified using image processing.

We will improve the technology for embedding digital watermarks in videos. [Solution] The system comprises a terminal device, a first server, and a second server. The terminal device transmits a first video to the first server. The first server embeds uniquely generated coded data into the first video received from the terminal device. The second server receives and stores the first video with the coded data embedded, and makes each stored video publicly available for viewing. The terminal device transmits an analysis instruction for the second video, which has been made publicly available by the second server, to the first server. In response to receiving the analysis instruction, the first server determines whether predetermined conditions are met based on the first video and the second video with the coded data embedded, and transmits information indicating the determination result of whether the predetermined conditions are met to the terminal device. The terminal device displays the determination result.

A system includes a hardware processor, and a system memory storing a software code. The hardware processor executes the software code to receive, from a user, a request related to a digital asset, obtain, from the user, verification data for use in creating a record of ownership of the digital asset, create, using the verification data, the record of ownership of the digital asset in an ownership database, embed a digital watermark into the digital asset to generate a digitally watermarked digital asset, and provide, to the user, the digitally watermarked digital asset. The digital watermark embedded in the digitally watermarked digital asset and the record of ownership of the digital asset in the ownership database enable ownership verification of the digital asset.

There is provided a computer implemented process for embedding a digital watermark within generated content, comprising the steps of: generating tokens from input data such as a user prompt using a Generative AI such as an LLM; and embedding the digital watermark within the set of generated tokens.

A system for generating derivative works comprises a content derivation platform with at least one processor configured to receive predetermined content and a request to transform it into a derivative work with a requested theme. The system uses generative artificial intelligence to create the derivative work comprising audio, video, or images based on the requested theme. A content approval machine learning model with a neural network determines an approval score based on content owner preferences and text embeddings identifying items in the derivative work. When the score exceeds a predetermined minimum, the system applies a digital watermark, configures an authorization server to govern use based on the digital watermark, and provides access to the approved derivative work. The requested theme may be determined through a chatbot interview using a Large Language Model. The generative artificial intelligence may comprise a diffusion model. The content may comprise music or audio.

The invention is suitable for the technical field of digital watermarking, and provides an embeddable real-time watermark superposition system and method, and the system comprises a front-end display layer, a reverse proxy layer, a WSGI encapsulation layer, a task scheduling module, a business processing service module, a data persistence layer, a message queue and an asynchronous processor. The business processing service module comprises an image batch watermarking subsystem and a video stream watermarking subsystem; the image batch watermarking subsystem is used for realizing batch watermarking processing of static images based on Pillow + SVG (Scalable Vector Graphics); the video stream watermark subsystem processes RTSP streams in real time based on FFmpeg and dynamically embeds watermarks, not only supports batch watermark processing of static images and videos, but also breaks the limitation of a traditional processing mode, realizes watermark superposition of real-time video streams, has complete operation capabilities of task management, query, cleaning and the like at the same time, and is high in practicability and high in practicability. And the method has high expandability and cross-platform deployment capability, and adapts to multi-scene actual requirements.

The invention discloses a Markdown Zip packaging method and a security enhancement method, and belongs to the technical field of document processing. According to the packaging method, a Markdown document and resources are packaged into a standard Zip container, an index.md main document, an assets resource directory and a manifest.xml list are contained in the standard Zip container, and document self-containing and transplantable rendering are achieved. On the basis, the security enhancement method integrates security mechanisms such as digital signature, AES-256 encryption, integrity verification and digital watermark tracking, and solves the problems that the existing Markdown document resource is easy to lose, the path is broken, no identity authentication exists and zero protection exists. According to the method, backward compatibility is kept, meanwhile, the Markdown document has enterprise-level safety capacity, and the method is suitable for technical delivery, knowledge management and high-sensitivity scenes.

This invention discloses a blockchain-based evidence storage hardware device for on-site auditing and evidence collection, belonging to the field of audit information technology. The device includes a main control processor, a multimedia acquisition unit, a satellite positioning module, a trusted timestamp module, a blockchain light node chip, a secure storage unit, a communication interface module, a power management module, and an anti-tamper detection module. The core innovations are: hash operations, timestamp generation, and on-chain writing are all completed in a dedicated chip trusted execution environment, with the private key bypassing the software layer; the timestamp module has a built-in hardware clock source calibrated with the National Time Service Center; the positioning module provides hardware-level spatial coordinates; data hash, timestamp, and coordinates are bound together and signed onto the blockchain to form an immutable evidence record; the anti-tamper module triggers private key erasure during unauthorized disassembly; the acquisition unit supports multimodal evidence collection and can embed digital watermarks. This invention achieves the goal of immediate evidence storage upon acquisition and a complete and verifiable evidence chain, enhancing the legal validity of audit evidence.

The present application belongs to the technical field of federated learning, and particularly relates to a decentralized federated learning training behavior supervision method based on digital watermarking technology. The present application comprises a task publisher initializing a global model and preparing a plurality of watermark data sets, and sending the initial global model and the watermark data sets to selected worker nodes; the worker nodes splice the local data sets and the watermark data sets and then perform local training to complete the embedding process of the watermark; the task publisher verifies the digital watermark, and according to the completion of the digital watermark, identifies the training honesty of the worker nodes. The present application aims at the problem that the worker nodes in the decentralized federated learning system architecture fake training results to affect the overall accuracy of model training, and through expanding the application scenario of digital watermarking, quantizes and visualizes the training behavior of each worker node, so as to achieve the purpose of promoting the worker nodes to keep honest in the training behavior, and provides trusted computing power support for the decentralized federated learning system.