286 results about "Digital watermarking" patented technology

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.

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.

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.

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 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.

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.

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.

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 relates to the technical field of data processing, in particular to an artificial intelligence-assisted password security policy dynamic adaptive adjustment method, which comprises the following steps of: acquiring login operation data to generate an encryption feature gradient; the aggregation server generates a dynamically updated federal reference model through a double-channel model updating mechanism, wherein a long-term model updating channel is fused with historical parameters to maintain system stability, and a short-term behavior time window channel dynamically adjusts recent gradient weight based on a time decay function. A graph computation engine generates a spatio-temporal composite risk score. And the risk decision engine generates a third-level response instruction. A risk misjudgment event is verified based on a response result, high-value training samples are screened to drive incremental training, space-time sensitive parameters are finely adjusted by a meta-learning optimizer, and noise is injected into a quantum gradient jammer to defend attacks. Optimized parameters are synchronized to a system module, and a closed-loop adaptive system is formed by combining homomorphic encryption transmission, model digital watermarking, quantum source hardware binding and anti-quantum signature.

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.

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 relates to the technical field of data management, and discloses a digital twin water plant cluster comprehensive visual management system. The system comprises a processing module, a modeling module, a process flow topology self-adaptive visual management interface and a flow control module, wherein the processing module carries out standardization processing on multi-source parameter data of a water plant to generate real-time data flow; the modeling module constructs a three-dimensional digital twinborn model by utilizing an oblique photography technology; the extraction module extracts spatio-temporal characteristics through multi-channel data fusion to obtain early warning information, the calculation module diagnoses abnormity based on a ternary association network and a heterogeneous graph attention algorithm, and the coding module generates a digital watermark health state code to form a predictive maintenance scheme. The panoramic display of the running state of the water plant, the accurate identification of the abnormal mode and the optimal configuration of maintenance resources are realized. According to the invention, panoramic display of the running state of the water plant, accurate identification of the abnormal mode and optimal configuration of the maintenance resources are realized, so that the overall running efficiency and management level of the water plant cluster are improved.

The invention relates to the technical field of archive data management, in particular to an accounting archive data management method and system and a storage medium. A block chain network architecture comprising a main chain and a plurality of side chains is constructed, the main chain is used for recording a transaction process, and the side chains are used for storing data; performing double encryption on the accounting file data through a homomorphic encryption algorithm and an attribute-based encryption algorithm; adopting a digital watermark to track data flow and verify data ownership; formulating a hierarchical storage strategy for the accounting archive data according to the sensitivity degree and the access frequency; a verifiable random function is introduced for data integrity verification; according to the invention, the block chain technology is combined with the encryption algorithm, the digital watermark and the hierarchical storage strategy, so that efficient and safe management of accounting archive data is realized; on the basis, the traceability of the data processing operation is improved, and the privacy security and the true integrity of the sensitive information in the accounting file data are further guaranteed.

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.

The invention relates to the field of digital copyright protection and transaction, in particular to a digital copyright protection and transaction system based on a block chain technology. The method comprises the following steps: combining a hash value of digital work content, a creation timestamp and copyright holder information to generate digital copyright information; dynamically adjusting the smart contract by using a smart contract dynamic adjustment algorithm, embedding a composite digital watermark in the digital work content, executing a transaction based on the updated smart contract, and monitoring the use condition of the digital work content; a multi-chain collaborative management mechanism is introduced, synchronization is carried out between a main chain and side chains, and loads between the main chain and the side chains are balanced. The problem that a single chain is difficult to deal with high-frequency copyright transactions and complex copyright management requirements is solved; the statically designed smart contract is difficult to adapt to rapidly changing market conditions in real time; the problems that defects exist in the aspect of preventing copyright infringement and tampering, comprehensive and effective copyright tracking and monitoring cannot be provided, and the copyright is easily removed or tampered by malicious users are solved.

The invention relates to the field of computers, in particular to a method and device for extracting watermarks. A digital watermark is embedded in a three-dimensional model, the risk that the three-dimensional model is illegally used can be reduced, however, the three-dimensional model is likely to be converted into two-dimensional data, an attack simulated by a neural network in the training process is generally an attack aiming at the three-dimensional model, and when the three-dimensional model is converted into the two-dimensional data, the form of the watermark is difficult to predict; effective watermarks are difficult to extract from two-dimensional data based on the neural network trained by the attack network. In the application, after the electronic device obtains the target file, the corresponding decoder in the neural network is used to extract the watermark based on the type of the target file, for example, the three-dimensional model decoder is used to process the three-dimensional model file, and the two-dimensional data decoder is used to process the two-dimensional data file, so that damage to the watermark caused by an attack means can be eliminated in a targeted manner, and the watermarking efficiency is improved. And the success rate of extracting the watermark from the attacked three-dimensional model is improved.

The invention provides a media data transmission method, device and system, and relates to the technical field of computers. A communication party serving as a sending end signs fingerprint information of media data sent previously, carries a signature value in a digital watermark and embeds the signature value in media data sent later. And the communication party serving as the receiving end verifies the signature value in the media data received later based on the fingerprint information of the media data received previously, so as to judge the authenticity of the media data transmitted previously. As the digital watermark is obtained based on the fingerprint information and the signature value of the media data, an attacker is difficult to counterfeit the digital watermark, and the secure transmission of the media data between two communication parties can be realized. In addition, the digital watermark generated based on the previously transmitted media data is embedded into the later transmitted media data, so that the fluency and real-time performance of media data transmission can be realized.

The present disclosure provides a neural network-based security defense method for encrypted multimedia data, including: adding implicit digital watermark information to original encrypted multimedia traffic to obtain watermark encrypted multimedia traffic; determining a first feature sequence of the watermark encrypted multimedia traffic; based on the first feature sequence and a second feature sequence of the original encrypted multimedia traffic, determining a correlation coefficient between the first feature sequence and the second feature sequence; and if the correlation coefficient indicates that a negative correlation between the first feature sequence and the second feature sequence satisfies a preset condition, performing training based on the first feature sequence and the second feature sequence to obtain a target neural network, where the target neural network is configured to identify whether there is implicit digital watermark information in encrypted multimedia traffic to be detected.

The present application relates to the technical field of computers, and provides a media data playback method and apparatus, a media data tracing method and apparatus, and a protection system. A terminal generates a digital watermark on the basis of authentication attribute information of media data to be played back, the digital watermark comprising the authentication attribute information and signature information obtained by signing the authentication attribute information with a target key. The target key is obtained on the basis of an identity private key held by the terminal and an authentication public key provided by an authentication party. The terminal embeds the digital watermark in the media data and plays back the media data embedded with the digital watermark. The authentication attribute information is used for identifying a playback source range of the media data, plays the role of identity information of the media data, and can reduce a traceability range of the media data. The signature information is used for ensuring the authenticity of the authentication attribute information of the media data. As long as the identity private key held by the terminal is not leaked, other user terminals will not be able to compute the target key, preventing others from maliciously impersonating the watermark to leak media data for entrapment.

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.

The invention discloses an anti-screen-shooting robust watermarking method based on a generative adversarial network and multiple tokens, and belongs to the technical field of digital watermarking. According to the method, firstly, watermark information is converted into image features through an encoder, the features are embedded into an original image, and a watermark image which is visually indistinguishable from the original image is generated; then inputting the watermark image and the original image into a discrimination network for feature analysis; in the training process, processing of simulating screen shooting distortion is applied to the watermark image; the watermark information is then recovered from the noise image by a decoder. According to the method, the coding mode of the watermark information is improved, and the robustness of the watermark in a real screen shooting environment is remarkably improved while the visual invisibility is ensured; especially, when the interference such as geometric deformation, moire and color distortion generated by screen shooting is handled, the integrity of the watermark data can be more reliably maintained, and high decoding accuracy is maintained.

In some implementations, there is provided a method comprising: receiving an image and a digital watermark; outputting a watermarked image generated based on the image and the digital watermark; selecting, from a set of benign transforms, a benign transform; selecting, from a set of malicious transforms, a malicious transform; performing the benign transform on the watermarked image to generate a benign image; performing the malicious transform on the watermarked image to generate a malicious image; decoding, by a decoder, the benign image to a first predicted value of the digital watermark; decoding, by the decoder, the malicious image to a second predicted value of the digital watermark; and adjusting at least one weight of the decoder during a learning phase of the decoder.

The embodiment of the invention discloses a low-altitude air signal lamp construction method and system. The low-altitude air signal lamp construction method comprises the steps that a GNSS module completes position positioning and clock calibration of a base station; the signal processing unit carries out digital watermarking on the signals and then sends the signals out, and simultaneously carries out digital label acquisition on the received signals so as to achieve the anti-counterfeiting purpose; the antenna transmits a signal; the low-altitude aircraft receives the signal and flies according to the signal. The method has the following advantages: 1, the traffic capacity of the six-direction air signal lamps at multiple height layers can be provided, and the cooperative sensing capacity of multiple aircrafts in a low-altitude high-density airspace is enhanced; 2, the supervision capability of an urban air traffic aircraft can be improved, signal lamp signals are encrypted, the safety of the signals is determined, and the low-altitude safe operation guarantee level is further enhanced; and 3, the technical architecture has expansion capability. And 4, in areas with high flight quantity and complex route structures, the surrounding operation situation awareness of the aircraft and the orderly and rapid passing of the aircraft at the intersection can be ensured.

The invention discloses a vehicle authentication detection task analysis system, and the system comprises a task management center which builds a mapping relation among contract entries, customer detection standards and an internal standard library; the sample car parameter intelligent processing unit is used for capturing data through an API (Application Program Interface) of the Ministry of Communications, verifying the integrity and performing deviation early warning on additional recorded parameters; the sighting judgment core engine is used for analyzing the multi-dimensional similarity between the sample vehicle and historical data based on a random forest algorithm; and the abnormal process control gateway drives the dynamic approval workflow and is connected with a short message platform to push an encrypted link and an overtime alarm. The system integration message middleware synchronizes CSS platform data in real time, the report generation module dynamically fills a detection result through an XML template and calls RESTful API signature, and batch asynchronous processing of historical reports and compression downloading of digital watermarks are supported. According to the invention, the problems of low task analysis efficiency, flow splitting and difficulty in compliance management in vehicle authentication detection are solved.

The present application relates to the field of computers, and in particular to a method and apparatus for extracting a watermark. Embedding a digital watermark in a three-dimensional model can reduce the risk of illegitimate use of the three-dimensional model. However, a three-dimensional model may be converted into two-dimensional data, and the attacks simulated by a neural network during training are usually attacks on the three-dimensional model. Thus, when the three-dimensional model is converted into the two-dimensional data, the shape of a watermark is difficult to predict, and a neural network trained on the basis of the described attack network is difficult to extract an effective watermark from the two-dimensional data. In the present application, an electronic device acquires a target file, and then on the basis of the type of the target file, uses a corresponding decoder in a neural network to extract a watermark, for example, using a three-dimensional model decoder to process a three-dimensional model file, and using a two-dimensional data decoder to process a two-dimensional data file, thereby eliminating in a targeted manner damage to the watermark caused by attack means, and improving the success rate of extracting a watermark from an attacked three-dimensional model.

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 a self-adaptive presswork binding method based on pressure feedback, and relates to the technical field of presswork binding. The method comprises the following steps: firstly, acquiring data such as a paper laminated structure and stress distribution by utilizing equipment such as a terahertz time-domain spectrometer, and analyzing paper components and coating thickness; secondly, combining a quantum annealing model with a digital twinning technology to optimize binding parameters, and predicting a wrinkle risk; during binding, the system establishes a pressure-displacement curve, piezoelectric ceramic micro-vibration friction reduction is adopted, and ultrasonic local softening is triggered if pressure is abnormal; after binding, detecting the quality by means of spectral domain OCT and Raman spectrum, and embedding a digital watermark; and finally, constructing a knowledge graph based on a graph neural network and a block chain, rapidly adapting to a new paper type through meta-learning, and realizing edge end deployment by using knowledge distillation. According to the scheme, the binding qualification rate is greatly increased, the equipment loss is reduced, the new paper adaptation time is shortened to 5 minutes from 2 hours, and the production efficiency is increased by nearly two times.

One aspect of the technology includes recovering image affine transforms via CNN-based classification and regression. Another aspect of the technology is a CNN-based network to detect a presence / absence of a digital watermark signal and recovery of affine transform coefficients associated with an image template. Other aspects, features and arrangements are also described and claimed.