148 results about "Digital fingerprint" patented technology

The systems and methods disclosed herein monitor application (e.g., artificial intelligence (AI) model) operations using interactions between the application and a kernel. The systems and methods disclosed herein intercept, using a kernel interface, one or more function invocations transmitted from the application (e.g., an AI model without model modification). Event record(s) are generated for one or more functions to define process identifiers, resource interaction types, timestamps, and / or resource identifiers. Observed pattern(s) for the application are identified by comparing current event record(s) with previous record(s), and the identified observed pattern(s) are evaluated against reference pattern(s) to generate score(s). Data packet(s) that indicate observed pattern(s), corresponding score(s), and / or cryptographic digital fingerprint(s) of the one or more functions are generated. The data packet(s) are transmitted to distributed ledgers for immutable storage.

The invention relates to the technical field of computer data processing, and discloses a cross-border e-commerce compliance tax refund method and an intelligent declaration system based on block chain evidence storage, and the method comprises the steps: constructing a reference library containing commodity physical attributes and fair density intervals; order transaction, logistics actual measurement and fund time sequence data are acquired; executing multi-dimensional cross validation based on the reference library, wherein the multi-dimensional cross validation comprises physical space logic verification based on geometric boxing simulation, attribute consistency verification based on density distribution matching and quality and time sequence joint verification; a risk level is determined by integrating results; and generating digital fingerprints for compliance data, writing the digital fingerprints into a distributed account book, and generating a declaration file by using an on-chain index. According to the invention, trade authenticity is verified through physical simulation and multi-dimensional logic, evidence is ensured not to be tampered in combination with a block chain technology, and compliance and auditing efficiency of tax refund declaration are effectively improved.

The invention discloses an archive information security storage and tamper-proof method and system based on a block chain, and belongs to the field of information security, the method comprises the following steps: obtaining archive information to be processed and generating standard archive data; a time sequence accumulation state hash model is adopted to process the standard archive data to generate digital fingerprints, and the time sequence accumulation state hash model constructs an academic state hash chain which takes initial academic state hash as a starting point and is recursively deduced along with time for each student; the generation of each new academic state hash is forced to depend on a previous academic state hash, a current period archive data abstract, a timestamp and a context challenge factor derived from a previous state; the digital fingerprints, the unique identity identifiers of the students and the operation metadata are packaged into archive information transactions, and the archive information transactions are signed by an authorization mechanism and then broadcasted to a block chain network; and a personal electronics file is formed. According to the invention, powerful and provable time sequence integrity is provided for auditing and tracing of archives.

The invention discloses a lightweight container X-ray intelligent security check method and system based on anti-distillation, and belongs to the technical field of image recognition. The method comprises the following steps: acquiring qualified image data, and respectively extracting metadata of the qualified image data to carry out hash verification marking for subsequent block chain evidence storage; generating a confrontation sample and a qualified image to form an enhanced data set; constructing a double-teacher confrontation distillation framework combined with a self-supervision pseudo-label generation mechanism, and after determining an optimal framework, completing model self-supervision training by using the enhanced data set as a training sample to obtain a target model; generating a model compression strategy of structured pruning and mixing precision quantification collaborative optimization, completing lightweight deployment of a target model, and executing an actual container security check task; a pixel-level risk heat map is generated according to X-ray image information obtained by an actual container security check task, and a risk assessment result is obtained; and generating a unique digital fingerprint record to the block chain by using a chain type evidence storage mechanism constructed based on the block chain to complete evidence storage.

The invention discloses a digital fingerprint generation method for terminal equipment, and relates to the technical field of digital fingerprint generation, comprising the following steps: S1, collecting multi-dimensional hierarchical features; s2, privacy enhancement; s3, fingerprint anti-regeneration generation is carried out; and S4, fingerprint life cycle management. According to the terminal equipment digital fingerprint generation method, multi-dimensional fine-grained feature acquisition is realized from a non-sensitive layer, a semi-sensitive layer and a high-sensitive layer, a feature weight is optimized through a federated learning framework, fingerprint drift caused by hardware replacement and software updating is effectively resisted, and the user experience is improved. Dynamic Gaussian noise is injected into numerical semi-sensitive features to balance privacy protection and feature effectiveness, 2048-bit key Paillier homomorphic encryption is adopted for high-sensitive features, meanwhile, cross-scene tracking risks are blocked through scenarized sub-fingerprint generation and an original feature immediate destruction mechanism, and the privacy protection and feature effectiveness are improved. And an anti-duplication architecture fusing a Merkle tree and a bloom filter is introduced to greatly reduce the fingerprint coincidence collision rate.

The invention relates to the field of Internet of Things data processing, in particular to a hydropower station IoT real-time data acquisition and uplink method based on edge computing, the core technology comprises data acquisition and preliminary screening processing of received data, and the screening processing method comprises a threshold detection algorithm and a moving average anomaly detection algorithm. Cleaning the data through a quartile distance judgment algorithm; judging and calculating the state of the equipment, and calculating the credibility of the data vector to obtain the running state of the equipment; data packaging and uploading: generating a data uploading block chain collected by a digital fingerprint combination through dual hash; the oracle machine establishes a contract rule to monitor the uploaded data in real time, and pushes abnormal information to the early warning platform when the data is abnormal, so that real-time early warning is realized; through the three-level architecture of edge calculation, the block chain and the oracle machine, on the premise of ensuring data credibility, the decision-making precision and the response speed are improved, and the three pain points of uncredibility, high delay and many false alarms in the industrial monitoring field are solved.

The invention discloses an electric energy metering box leakage protection switch trip detection method, which comprises the following steps of: when power failure is detected, generating event context data under the constraint of limited energy based on multi-mode original data, execution energy and buffer combined arrangement; executing short window early warning analysis to obtain an early warning trigger instruction and an early warning feature set; and responding to the early warning trigger instruction, constructing a transient fingerprint and executing parallel crosstalk decoupling to obtain a transient fingerprint and decoupling conclusion. The fingerprint construction adopts logarithmic time scattering fingerprint and electric arc physical fitting, and the decoupling adopts geometric constraint sparse chromatography decoupling to identify a responsibility loop. And fusing the transient fingerprint, the decoupling conclusion and the early warning feature set, applying a multi-modal time sequence consistency constraint, and forming a tripping conclusion and a leakage protection type suggestion. According to the method, the technical problems of loss of evidence at the moment of tripping power failure and strong crosstalk of parallel loops are solved, the responsibility loop can be positioned with high confidence, and interpretable tripping mechanism diagnosis and type suggestions are provided.

The invention relates to the technical field of bill risk assessment, and discloses a bill circulation process risk assessment block chain system and method. The method comprises the following steps: in a block chain node network initialization stage, establishing a bill feature classification library and a circulation path topological structure; and when a bill circulation event is detected, extracting the bill digital fingerprint and the identity label of the current holder. According to the risk weight coefficient in the digital fingerprint matching feature classification library, the credit rating data is inquired in combination with the identity, and the two are input into a dynamic evaluation model to generate an initial risk evaluation value; and calculating a path complexity index based on a flow path topological structure, dynamically correcting the initial evaluation value according to the path complexity index, and outputting a final risk score. According to the method, distributed storage and sharing of bill information are realized based on the block chain, dynamic evaluation and path complexity analysis are combined, a bill circulation risk evaluation effect is optimized, and bill market risk management and control requirements are met.

The invention relates to the technical field of traceability of a meta-universe platform, and discloses an agricultural product traceability system and method based on the meta-universe. According to the method, firstly, key events such as harvesting, farming operation, quality inspection and transportation of agricultural products in the whole process from planting to selling are automatically collected through a collection end, parameters and evidence hash values are spliced, a data abstract is calculated, digital signature is carried out, and it is ensured that a data source is credible; the gateway carries out triple defense line verification on the received data packet; then the data association module performs knowledge graph construction on the discrete events passing verification, quantifies the credibility of the causal relationship through multi-dimensional weight calculation, and finally determines a main causal path representing the most credible life trajectory; and finally, the upper chain traceability module adopts a mixed architecture of a Merkle tree and distributed storage, generates a digital fingerprint from the key information of the main path, stores the digital fingerprint in a block chain, stores a complete evidence packet in an IPFS, and finally provides immersive traceability experience capable of being verified by one key for consumers in the meta universe to form a closed-loop credible traceability chain.

The present application relates to the technical field of artificial intelligence technology and blockchain technology, specifically to an intelligent copyright protection and infringement identification method for students' innovative works, aiming to solve the problems of no traceability in the creation process, poor adaptation of multi-type works, difficulty in deep infringement identification, blurred boundaries of AI-assisted creation, and low adaptability in the campus scene in the prior art. The method comprises: receiving the innovative works uploaded by students, extracting multi-modal main features and auxiliary features according to the type, and generating a unique digital fingerprint through feature distillation fusion; recording the whole process of creating tracks, and combining time sequence blockchains to generate a timestamped evidence certificate. The present application realizes the whole process of copyright protection for students' innovative works, adapts to various types of works such as text, code, vision and multi-modal combination, has high accuracy in infringement identification, is convenient and low in cost, is suitable for large-scale popularization and application in the campus, and provides strong support for students' rights protection.

The embodiment of the invention provides a data auditing method and device, equipment, a storage medium and a program product, relates to the technical field of data processing, and can be applied to the field of financial science and technology. According to the method, a hash value of an operation log is stored in a private block chain network, then a digital fingerprint corresponding to the operation log is determined based on the hash value, then abnormity auditing is performed on the operation log based on the hash value of the operation log in the private block chain network and an auditing contract, and when it is determined that a target operation log is abnormal, the operation log is subjected to abnormal auditing. And verifying the target operation log based on the target digital fingerprint corresponding to the target operation log in the public block chain network, and generating an audit report of the target operation log when the verification is passed. According to the method, the hash value of the operation log and the auditing contract are stored in the public chain, on the basis that the compliance requirement of the financial industry for data storage is met and auditing credibility is ensured, automatic auditing is achieved, and the storage cost is reduced.

The invention relates to the technical field of federated learning, and discloses an image omics-oriented cross-domain federated machine learning training method, which comprises the following steps that: a server distributes a global orthogonal semantic base to establish a shared gradient space recessive semantic coordinate system, and when the stability of a local training process meets a preset condition, a client sends the global orthogonal semantic base to the client; a local gradient is projected to a coordinate system and uploaded together with a digital fingerprint representing the physical characteristics of imaging equipment, and a server groups clients according to the digital fingerprint and performs weighted aggregation based on the information concentration degree on received projection vectors in each group so as to reconstruct a global gradient to update a model. According to the method, through an aggregation mode of firstly performing grouping according to physical causes and then performing weighting in groups according to information values, systematic deviation from equipment differences and real pathological semantics from data contents can be effectively stripped, and sensitivity to key clinical features is kept.

The invention relates to a method for identifying vehicle license plates in ticketless car parks, in which, as a digital fingerprint of the license plate, a raw evaluation matrix is used, which is obtained in a character recognition phase, as a step prior to generating the read of the license plate and an evaluation matrix converted into a character string. The invention also proposes a method for comparing two or more license plates and a method for managing ticketless car parks.

This disclosure provides a data processing method and related equipment based on deep learning, relating to the field of intelligent recommendation technology. It includes: acquiring graph structure data corresponding to a set of items, and determining a target item node and a set of neighboring item nodes based on multiple item nodes in the graph structure; identifying a subset of feature data from the feature data of the item set that is inconsistent with the neighboring feature data of the target item node; matching digital fingerprints to the feature data in the feature data subset and determining the similarity between the feature data and the digital fingerprints; filtering based on similarity, storing feature data that meets preset conditions in a uniform pool corresponding to the target item node, and aggregating the feature data in the uniform pool to generate updated target feature data for the target item node; and determining user preferences based on the updated target feature data of at least one target item node. This disclosure can reduce computational complexity and improve computational efficiency.

The application belongs to the technical field of blockchains, and particularly relates to a compliance data credible storage and traceability system based on digital fingerprints and alliance chains, which comprises a data preprocessing and structured slicing module, a multi-level digital fingerprint construction module, an alliance chain consensus storage module and a compliance verification and traceability module. The data preprocessing and structured slicing module is used for data standardization and slicing. The multi-level digital fingerprint construction module is used for constructing a Merkle tree based on a slicing fingerprint and extracting a global fingerprint. The alliance chain consensus storage module is used for encapsulating the global fingerprint and metadata and storing encrypted slices in a distributed file system. The compliance verification and traceability module is used for realizing data verification and tampering accurate positioning by using a Merkle path proof. The multi-level hash structure improves large-scale data verification efficiency, the selective disclosure mechanism solves the conflict between privacy protection and compliance audit, and the alliance chain consensus mechanism ensures the whole life cycle safety and credible traceability of electronic data storage.

The application discloses a data privacy protection method and a detection method for a privacy-enhanced semi-blind digital fingerprint, combines a differential privacy technology and a digital fingerprint technology, embeds carefully designed noise into specific positions of a numerical aggregate data set, can realize fingerprint embedding and noise interference operation on carrier data in one step, and ensures protection of private information in the carrier data set and tracking function on traitors.

The application discloses a kind of based on alliance chain's drawing life cycle evidence method and system, the method includes: the drawing to be stored in evidence is divided into multiple drawing blocks, the numerical characteristics of each block and are normalized, the numerical value of the whole and each drawing block of the drawing to be stored in evidence is matrixed, and the drawing digital fingerprint of the drawing to be stored in evidence is generated by digital fingerprint generation model;When the drawing to be stored in evidence is modified or updated, obtain the modification matrix difference, and through drawing version evolution model, the evolution value of each drawing version is calculated in conjunction with drawing digital fingerprint;For each access user, according to the identity key of user, authority level, drawing digital fingerprint and the evolution value of each drawing version, the authorized value of user access each drawing version is calculated, and according to authorized value, it is judged whether user can access corresponding drawing version.

This invention discloses an AI design generation link management method based on blockchain notarization, relating to the field of design link notarization technology. The method includes: generating rule summaries and calculating rule drift indices; accessing reference materials, standardizing them, and generating material fingerprints and access control identifiers; calculating material anchoring completeness indices to form material anchoring; collecting generation parameters, modification actions, referenced material anchoring, and output file information at inference trigger points; encapsulating metadata packets and calculating fused digital fingerprints; signing the metadata packet summary; writing the fused digital fingerprint, metadata packet summary, output file set summary, and version parent association summary into the blockchain to obtain a trusted timestamp and generate an electronic copyright certificate carrier; releasing design data based on approval and double signature, recording delivery usage, and forming a periodic settlement summary on the blockchain; verifying online in case of disputes and uploading the verification summary and revocation record to the blockchain to achieve full-link non-repudiation and traceability.

The application relates to a method and system for automatically identifying defects on a radiographic inspection film, belonging to the technical field of nondestructive testing. The method comprises collecting the film to obtain a digital image; based on the structural features of the weld, the image is preprocessed by partitioning, the weld area, heat-affected zone and base material background are identified and segmented, and different image enhancement strategies are adopted for different areas; the preprocessed image is input into an improved deep learning model combining the YOLOv8 target detection network and the U-Net segmentation network for detection, and the positioning, classification and contour segmentation information of the defects are output; based on the pre-set confidence threshold, the identification results are filtered and distinguished as clear defects and suspicious defects; a film evaluation report is generated, and the digital fingerprint of the film image is calculated, the fingerprint and the report are encrypted and uploaded to the blockchain storage for subsequent authenticity verification. The application realizes full automation and intelligentization of the film evaluation process, improves the identification accuracy and efficiency, and ensures the credibility and non-tamperability of the detection results.

The application discloses an automatic audit report generation full-process method based on a large model. The application avoids the illusion and content omission problems that are easily caused by a single large language model when processing massive heterogeneous data and complex logic at one time by decomposing a complex report preparation task into multiple independent and professional subtasks, combining the dynamic coordination of the task scheduling matrix, introducing a prompt engineering and post-check mechanism, and strictly correcting the logic, smoothing the text, and standardizing the professional terms of the preliminary audit text. The application filters the possible rough expressions and logical jumps in the content generated by the large language model, ensures that the target audit report file produced has factual accuracy and logical consistency, and guarantees the uniqueness, tamper resistance, and full-process version traceability of the target audit report file issued through the automatic rendering of the document structure tree and the generation of digital fingerprints, thereby meeting the requirements of audit archive compliance management.

The application discloses a digital delivery management platform and method based on BIM technology, and relates to the technical field of digital delivery, which comprises the following steps: according to an LOD-LOR rule dictionary and a progress mapping table, performing geometric and logical consistency checking on BIM models by components, identifying missing items and conflicts, and generating a high-trust model after repair; based on the high-trust model, combining professional zoning and work breakdown structure WBS to divide delivery units and generate a delivery dataset; performing field normalization, hierarchical hashing and signature operation on the delivery dataset to generate a verifiable delivery package with a digital fingerprint, and obtaining the digital fingerprint, signature record and hash index table; based on the digital fingerprint and signature record, importing the verifiable delivery package into a digital delivery platform, verifying consistency by combining the hash index table, generating a delivery verification report and storing the report as a digital archived achievement. The application makes the BIM digital delivery process have high trustworthiness and verifiability.

The invention discloses a wooden artwork source digital identity authentication method based on CT scanning. According to the technical scheme, the wooden artwork source digital identity authentication method is characterized by comprising the steps that S1, multi-row spiral CT or industrial micro-focus CT scanning equipment is selected according to the size of an artwork to obtain three-dimensional volume data; s2, performing image reconstruction preprocessing and feature region extraction on the three-dimensional volume data to obtain an artwork feature image; s3, analyzing a macroscopic structure feature, a mesoscopic texture feature, a microscopic detail feature and a feature image set of the to-be-authenticated artwork; s4, setting a unique identity code, and generating a digital identity file of the artwork; s5, obtaining feature parameters and digital fingerprint vectors of the artwork according to the feature image set; s6, inputting the digital fingerprint vector into an artwork authentication model, and outputting an authentication result corresponding to the artwork according to the authentication model; and a digital identity certificate and a block chain evidence storage record are generated according to the authentication result. According to the invention, the safety and reliability of identity authentication of the wooden artwork are improved.

The invention relates to the technical field of data processing, and discloses a ship traffic data safety management method and system, and the method comprises the steps: collecting AIS data, radar data, VHF data and hydro meteorological data, obtaining an original data package, generating a digital fingerprint for the collected original data package through a block chain technology, and carrying out the chaining and evidence storage; identifying and filtering abnormal data in the original data packet through a hybrid algorithm based on an isolated forest and a variational auto-encoder to obtain processed data; based on the ship position, the navigation area risk level and the data type corresponding to the processed data, an AES-CHACha20 adaptive encryption algorithm based on spatio-temporal context perception is adopted, and an encryption key is dynamically bound with spatio-temporal information; constructing a ship traffic space-time risk portrait, and distributing data access authority in real time through a dynamic authority adjustment algorithm in combination with a user role, an operation scene and a real-time risk level; according to the invention, the ship traffic data safety protection capability is obviously improved.

The invention discloses a system and a method for managing data of equipment with a body based on a block chain and federated learning. The system comprises the equipment with the body, the block chain and an aggregation server, the equipment with the body collects data and generates a data asset package during operation, creates a digital fingerprint of the asset package and writes the digital fingerprint into the block chain; the aggregation server starts federal learning through the model training request, so that each node is trained locally and the encrypted model parameters are uploaded; the aggregation server aggregates parameters to update the global model; and the block chain automatically distributes incentives to the data contributors participating in the training. Therefore, by adopting the embodiment of the invention, the security of data circulation is improved. And meanwhile, the rights and interests of data creamers are clarified, and accurate matching of contribution and return is realized, so that continuous contribution of high-quality data is effectively stimulated. And meanwhile, core data of different subjects do not need to be exposed, so that the ecological level of the intelligent agent can be effectively improved while privacy and commercial secret are protected.

System and Method for Contextual Relationship-Analytics A computer-implemented relationship-analytics system ingests time-stamped multimodal communication between a first and second human subject together with public-web persona data and first-subject annotations. Natural-language processing transforms the combined corpus into (i) an attachment-style vector that classifies anxiety-avoidance orientation and (ii) an affinity-language vector that identifies a dominant affection modality. Both vectors are stored in typed fields of an Emotional Digital Fingerprint (EDF) record. Concurrently, a wearable sensor supplies a biosignal, which is digitized to compute a normalized Balance-Load Index (BLI) tagged with a precise time-stamp. The BLI is correlated with co-occurring interaction data within a configurable window; correlation weights update the stored vectors, and a link identifier tying the BLI to its interaction subset is persisted in the EDF. An inference engine reads the updated EDF to output probabilities of long-term compatibility and incompatibility, which are transmitted to a client device for user guidance.

Presented herein are systems and methods of evaluating network operations associated with computing systems. A server may receive, from a computing system, an electronic request to execute a first network operation using a plurality of attributes provided by an end user device to the computing system. The first network operation may be initiated via the end user device. The server may retrieve (i) a digital fingerprint associated with an identity of the computing system and (ii) a plurality of network operation metrics associated with the computing system. The server may execute, using the digital fingerprint and the plurality of network operation metrics, a machine learning (ML) model to generate a likelihood of fraud caused by the computing system. The server may, in response to the likelihood of fraud satisfying a threshold, execute a second network operation using the plurality of attributes, instead of executing the first network operation.

The invention discloses a bamboo cellulose preparation raw material inventory management system based on a block chain, particularly relates to the field of chain inventory management, and is used for solving the problems of quality attenuation, cross-warehouse allocation and low transaction triggering intelligence degree of traditional bamboo cellulose raw materials in a storage cycle. The method comprises the following steps: constructing a raw material digital fingerprint by collecting core physical characteristics and batch information of a bamboo cellulose raw material; predicting the quality change of the next transaction time window based on the quality dynamic attenuation model in combination with the storage environment parameters, and exposing the risk in advance; when the attenuation amplitude exceeds a threshold value, automatically entering on-chain auction, and electing a transaction object according to anonymous bidding and reputation weight; and for the inventory of the continuous flow beat, calculating an allocation priority index through a global inventory map and automatically executing cross-warehouse allocation. According to the mechanism, credible recording, dynamic early warning and automatic decision making of the whole inventory management process are achieved, and the raw material circulation efficiency and the quality management capability under multi-warehouse cooperation are improved.

1. Name of the product in this design: Face and fingerprint access control machine (XF3). 2. Purpose of this design: To be installed on various security doors and to unlock the door electronically via digital fingerprint or facial recognition. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention relates to the technical field of image recognition and block chain evidence storage, and discloses a block chain management system for plastic batch traceability and performance prediction. The invention aims to solve the problems that the identity label of the bulk plastic raw material is easy to lose and the traditional detection is lagged and the trust is lost. According to the method, a plastic unit microscopic image is obtained through multi-angle dark field imaging, and a standardized morphology graph is generated through self-adaptive segmentation; extracting texture features to generate a unique digital fingerprint, identifying microdefects and deducing a performance prediction score; and finally, recording the encrypted fingerprint and score to the block chain. According to the method, the unique identity label is established for the bulk material based on the microscopic visual features, non-destructive real-time performance pre-judgment is realized, the non-tampering property of traceability and quality data is ensured by utilizing the block chain, and a credible closed-loop management mechanism is constructed.

This invention relates to the field of copyright tracing technology, and proposes an automatic tracing management method and system for film and television copyright chains based on OCR and AI. The method includes: responding to a copyright tracing request, obtaining a sample of the film or television work to be traced, and extracting a sequence of visual keyframes. Optical character recognition is performed on the keyframes to obtain explicit copyright text, and implicit copyright feature codes are extracted from the pixel distribution. The explicit copyright text is segmented and verified to obtain the copyright holder's identity, unique serial number of the work, and authorization validity period fields. The implicit copyright feature codes are decoded to obtain the copyright registration timestamp and distribution channel identifier fields. The above fields are integrated to generate a copyright statement record, and a digital fingerprint is generated by combining the visual hash value. The digital fingerprint is submitted to a smart contract on a pre-set film and television copyright blockchain, and the fingerprint record of the original work is matched and obtained. Copyright ownership information and historical authorization flow chains are read from this fingerprint, and the copyright tracing result is finally confirmed. This invention can improve the efficiency of film and television copyright tracing management.