158 results about "Bloom filter" patented technology

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.

A control method includes dividing a source data unit among a plurality of source data units received from a host into a plurality of source chunks; generating a unique value for each of the plurality of source chunks; inserting the unique values into a source bloom filter of the source data unit; calculating a Hamming similarity with a storage bloom filter of each of the plurality of active storage data units for the source bloom filter; selecting an active storage data unit based on the highest Hamming similarity as a target data unit; classifying each of the plurality of source chunks as a first deduplicated chunk, an already deduplicated chunk, or a unique chunk using the unique values; and storing at least one of the first deduplicated chunks in the target data unit, such that spatial locality of each chunk may improve and fragmentation may be alleviated.

Disclosed is system for fulfilling service request using computing nodes. The system comprises a decentralized computing network, comprising computing nodes operating as autonomous agents, configured to implement software framework comprising: client-agent device 5 configured to: receive service request and generate objective therefor, and send objective to agent-device configured to send queries to a machine learning model agent and / or obtain tasks, and list of autonomous agents associated with objective; and processing arrangement configured to: generate directed acyclic graph (DAG) having 10 nodes representing first task and edges representing dependency of first task on second task(s) amongst tasks, and initialize Bloom filter of each node to track completion status of second task(s). Autonomous agent is configured to: identify second task(s), check completion status of second task(s), using Bloom filter of first task, upon completion of second 15 task(s), execute first task, and update Bloom filter.

The invention discloses an identification-based lightweight hierarchical trust access authentication method and system, and mainly relates to the technical field of network security. Comprising the following steps: in an offline stage, an electric power registration center generates a private key root bound with an identity for a terminal through identity-based cryptography, a key generation center derives a lightweight work key voucher and pre-calculates verification points of all terminals, and a unified main multi-dimensional Bloom filter is constructed and distributed to a main station; in the online stage, a terminal updates a key and generates a signature only through hash operation, a master station reconstructs candidate verification points after receiving a message, and non-interactive verification is completed by locally querying a master multi-dimensional bloom filter. The method has the advantages that unification of strong identity credibility and extreme light weight of the terminal is achieved, the terminal side only needs efficient Hash operation, the server supports high-concurrency and low-delay authentication through the pre-calculation and Bloom filter technology, and the problem of safe access of massive distributed terminals in the electric power Internet of Things is effectively solved.

The invention discloses a threshold intersection-oriented efficient multi-party privacy set intersection method and system, and belongs to the technical field of privacy computing. Comprising the steps that m participants are initialized, and each participant holds n to-be-solved private data sets; m secret keys are generated, and after the element blinding factor r is selected, the first m-1 secret keys are sent to the corresponding secret keys respectively; each participant carries out partial OPRF value calculation and sends the partial OPRF value to the cloud server through OKVS; after the cloud server carries out OKVS decoding, the OKVS decoding is constructed into a matrix M with the dimension as shown in the specification; the cloud server performs reconstruction calculation according to the matrix M, inserts the matrix M into a Bloom filter and sends the matrix M to the Bloom filter; and querying in the Bloom filter fed back by the cloud server, if the Bloom filter exists, determining that the Bloom filter belongs to the intersection, and if the Bloom filter does not exist, determining that the Bloom filter does not belong to the intersection. Threshold homomorphic encryption does not need to be used for calculation, and the trusted cloud server is introduced to bear part of calculation load, so that the calculation overhead of the protocol is greatly reduced.

The application discloses a privacy risk detection method, device and equipment of a medical RAG system and a storage medium, wherein a cascade design of a Bloom filter and a MinHash is used to greatly reduce the similarity detection complexity on a large-scale document set, millisecond-level response can be realized under typical hardware conditions, the delay is low, the online medical RAG scene is suitable, not only the text surface similarity is considered, but also medical entities and identifiable information are comprehensively analyzed to form a multi-dimensional risk score, which helps to reduce missed detection and false positives, the detection accuracy is high, the fine-grained risk score and level can be output for each query, resource consumption is controllable, easy to expand, and system integration is friendly.

The application discloses a multi-keyword fuzzy ciphertext retrieval method and system, wherein the method comprises the following steps: decomposing a search request to generate a plurality of query keywords, generating a plurality of query vectors and a plurality of keyword trapdoor functions corresponding to the plurality of query keywords according to the plurality of query keywords; traversing the plurality of keyword trapdoor functions through a plurality of document encryption indexes constructed in advance, respectively calculating the sum of inner products of each document encryption index and each keyword trapdoor function, and obtaining a plurality of similarity values between the plurality of query vectors and the document encryption indexes; comparing the plurality of similarity values, and obtaining a document corresponding to the search request according to a comparison result. Thus, the problems that the retrieval scheme of the related art cannot effectively eliminate the false hits of the Bloom filter, the precision is low, the extracted keyword feature dimension is small, and the feature is degraded after dimension reduction of the keyword feature vector, so that the fuzzy keyword retrieval cannot be realized with high precision and the usability is low are solved.

The invention relates to a message broadcast deduplication method and device based on a Bloom filter and computer equipment, and the method comprises the steps: judging whether a message is processed or not based on a local message state record after a downstream node receives the message and corresponding path information sent by an upstream node; the message state is recorded as a counting Bloom filter storing the processed message; when it is judged that the message is not processed, the message state record is correspondingly updated; and determining a forwarding target corresponding to the downstream node according to the path information so as to broadcast a message to the downstream. Through the application, the message state record table can be continuously and stably maintained through the counting bloom filter, the node is prevented from repeatedly processing the message, and the downstream node can optimize the broadcast path according to the corresponding path information of the message, thereby avoiding message redundancy in the broadcast process, and improving the broadcast efficiency. And a stable and effective message broadcast deduplication method is realized through a two-layer deduplication mechanism.

The application relates to the field of privacy protection query schemes, in particular to an indoor multi-user personalized spatial keyword privacy query method based on a GIS enhanced index tree. In view of the demand of multi-user spatial keyword privacy query in an indoor environment, a GISEnhancedIndexTree index structure is constructed by fusing Hilbert coding, an R tree, an encrypted Bloom filter and an EASPE encrypted vector, and spatial and text information of indoor objects are encrypted and indexed. During query, a user request is encrypted and processed into a trapdoor, a server performs spatial, floor and keyword pre-filtering in the index tree according to the trapdoor, calculates the similarity of encrypted vectors by means of EASPE, and returns the encrypted result to the user after threshold filtering, score aggregation and sorting. Meanwhile, a comprehensive position vector construction method and a privacy protection coordinate conversion method based on a local coordinate system are designed to guarantee the privacy safety of the whole data flow. The method can effectively protect the privacy of users and improve the efficiency and accuracy of indoor multi-user personalized spatial keyword query.

The invention discloses a privacy set intersection method and system supporting load interval screening, and the method comprises the steps: determining a Bloom filter and a hash function, generating a homomorphic encryption key pair by a first participant, setting a threshold parameter and a load interval by a second participant, and generating a symmetric encryption key, a master secret and a random number; the first participant obtains a ciphertext and sends the ciphertext to the second participant, the second participant generates a homomorphic ciphertext, and the second participant encrypts elements, a load value and a load interval boundary value of the homomorphic ciphertext and sends the elements, the load value and the load interval boundary value to the first participant together in combination with a threshold parameter; the master secret is recovered through threshold judgment; the first participant decrypts and screens out the intersection element ciphertext meeting the load interval, and sends the intersection element ciphertext to the second participant; and outputting the intersection element meeting the load interval condition through decryption. According to the invention, intersection calculation of load values in a specific range is realized.

The application relates to the technical field of software development, in particular to a non-invasive dynamic burying point system for an application, an implementation method and a storage medium. A starting class is defined for a burying point application, the starting class is connected to a process after the burying point application is started, and a transformer module encapsulated into a java agent is loaded. Compared with an existing annotation-based invasive burying point scheme and a static instrumentation burying point scheme, the application is effective for any jvm application, meanwhile, targeted burying point optimization of common framework and tool class libraries and progressive burying point processing of specific scenes are considered; a classification process is generally mainly aimed at methods of the application itself, and existing classification can be generally adopted for widely used library classes. When the application needs to change or cancel burying point logic, only the black and white list classification and the processor associated with the white list need to be changed, and the server side is re-calculated according to the black list to obtain the bloom filter parameter, so that the operation is simple, the burying point is flexible, and the application is not aware of the burying point.

The systems and methods disclosed herein orchestrate task execution among autonomous (or semi-autonomous) AI agentic models (“agents”) responsive to a received query by using a hierarchical semantic fingerprinting framework to generate semantic-aware fingerprints for the query and agents. Queries and descriptions of agent capabilities are processed by a series of hierarchical levels using locality-sensitive hash (LSH) functions, where subsequent layers encode more complex semantic information and generate longer hash values. The hash values are aggregated into a semantic fingerprint. A bloom filter cascade uses a series of increasingly accurate hierarchical bloom filters to reject agent fingerprints that differ from the query fingerprint. The remaining agent fingerprints are compared bitwise to the query fingerprint, and those closest to the query fingerprint are selected to generate a routing path for the query. Responses from the selected agents are aggregated into an output that is responsive to the input.

Embodiments of the present specification provide a method and device for determining whether query data belongs to a target data set, which is implemented by using multi-party secure computing technology to achieve privacy protection and achieve the purpose of anonymous query. The method comprises: a first party determines a preset number of target positions corresponding to the query data in a Bloom filter, extracts encrypted elements of the preset number of target positions in a first ciphertext array obtained from a second party, and obtains a preset number of encrypted values; the first ciphertext array is obtained by mapping the target data set to the Bloom filter by the second party, and each element in the first array is homomorphically encrypted; a homomorphic function operation is performed on the preset number of encrypted values to obtain a result ciphertext; the homomorphic function operation is used to aggregate the element values of the preset number of target positions; and the result ciphertext is sent to the second party, so that the second party decrypts the result ciphertext and determines whether the query data belongs to the target data set according to the decryption result.

The embodiment of the invention provides a revocable attribute-based encryption method based on a block chain and policy hiding, and belongs to the technical field of data security. Comprising the following steps: constructing an access strategy, generating a symmetric key, encrypting a data file and the symmetric key, and outputting an intermediate ciphertext; replacing an access strategy in the intermediate ciphertext through a Bloom filter, outputting a final ciphertext and a ciphertext header component, and storing a hash value of the final ciphertext to a block chain BC; verifying a decryption token for applying for accessing the data file by the data user DU; if the verification is passed, judging whether the attribute set of the data user DU is in a revocation list; under the condition that the attribute set is not in the revocation list, verifying whether the attribute meets an access strategy or not; if yes, executing an outsourcing decryption operation, and returning a part of decryption result to the data user DU; verifying the correctness of the partial decryption result according to a hash value stored on the block chain BC; and if the verification is passed, final decryption is carried out to obtain a plaintext data file.

Methods and apparatus to estimate cardinality across multiple datasets represented using Bloom filter arrays are disclosed. Disclosed examples include processor circuitry to execute and / or instantiate instructions to determine an inclusion-exclusion expression that defines an audience size for a user group of interest. Terms in the inclusion-exclusion expression corresponding to either a first cardinality of a first one of at least three Bloom filter arrays or a second cardinality of a union of two or more of the Bloom filter arrays. Different ones of the Bloom filter arrays representative of different sets of users who accessed media. The at least one processor further to estimate, based on the inclusion-exclusion expression, the audience size of the user group of interest.

The application provides a heat-aware storage engine performance optimization method, which comprises the following steps: determining a target database, initializing a maximum heap in the memory of the target database, and maintaining the file heat of the system; reading file heat information from the log of the target database, and recovering the file heat identification mechanism based on the maximum heap; writing the file heat information into a Memtable of an LSM-tree memory component by a storage engine, and making the data of the Memtable fall to the disk and generate a CuckooTable file; establishing a Bloom filter for the CuckooTable file on an NVM; recording the corresponding relationship between the Bloom filter and the file in an index queue; and updating the index queue when the number of files in the LSM-tree reaches a preset threshold. The method provided by the application can be used to optimize the performance of a storage engine designed with a LSM-tree structure.

A centralized database management system performs data synchronization with lower bandwidth consumption and higher efficiency. The system manages data synchronization and data reconciliation across multiple databases managed by multiple DBMS across different client servers. The system generates and sends instructions that encode each data table into an invertible bloom filter and identifies differences between the two databases by performing a subtraction operation on the two invertible bloom filters. The system may generate a third invertible bloom filter comprising information associated with differences between the two data tables. The system may send instructions to the source and the destination databases, where a first and a second invertible bloom filters are encoded for the source and the destination databases, respectively. The system may decode the third invertible bloom filter, identify the different elements, and generate instructions to the source and / or the destination database.

The invention discloses a fund transaction anti-fraud interception method, device and equipment and a storage medium, and relates to the technical field of electronic fund transactions, and the method comprises the steps: receiving a Bloom filter generated based on a suspicious account list; when a fund transaction is accepted, a transaction account is preliminarily filtered based on a Bloom filter, and a suspicious account list in the transaction account is determined. And judging the suspicious account list, and determining the hit suspicious account list. And carrying out secondary filtering on the transaction accounts in the hit suspicious account list to obtain a verification result, and executing transaction interception or release operation according to the verification result to realize fund transaction fraud prevention interception. Through the above mode, on the premise that the performance of a fund transaction system is not affected and the complexity of a fund transaction link is not increased, suspicious transactions are accurately identified in massive online fund transactions, suspicious fund flow is effectively blocked, and the fund security of a user is protected.

The invention relates to a resource transfer data processing method, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a first resource identifier and a second resource identifier corresponding to resource transfer data to be processed; the identification precision of the first resource identifier to the resource transfer data is greater than the identification precision of the second resource identifier to the resource transfer data; under the condition that the first resource identifier is not matched in the processed resource identifiers, matching the second resource identifier with the target Bloom filter to obtain a matching result; the target Bloom filter is obtained by performing data writing on the initial Bloom filter according to a historical resource identifier corresponding to the historical resource transfer data; and under the condition that the matching result indicates that the second resource identifier is matched with the target Bloom filter, generating a duplicate checking result of the resource transfer data through a preset duplicate checking rule. By adopting the method, the weight checking intelligence of the resource transfer data can be improved.

The application relates to an equivalent connection query method and device for a ciphertext database, which comprises the following steps: constructing indexes corresponding to a plurality of tables; wherein the indexes comprise encrypted inverted index tables, and the inverted index tables are generated from original tables; uploading the encrypted indexes and a multi-set Bloom filter to a server; wherein the multi-set Bloom filter is obtained according to all values of inserted connection attribute columns; sending an equivalent connection query request of a user to the server, so that the server returns corresponding equivalent connection query results to the user. Compared with the prior art, the multi-set Bloom filter has shorter solving time and higher efficiency, and can hide the relationship between sets in a table and a Bloom filter, thereby hiding external memory access modes, significantly improving the throughput of data processing, reducing the number of interactions with a trusted execution environment, and effectively solving the problem of large communication overhead.

The invention provides a method and a system for generating a logic execution plan, which can be applied to the technical field of computers. The method comprises the following steps: firstly, generating a first logic execution plan according to a data query request; wherein in the first logic execution plan, a first association operation exists between the first table and the second table, and a second association operation exists between the second table and the third table. Then, adding a first Bloom filtering operation between the first table and the second table to obtain a first filtering result, and adding a second Bloom filtering operation between the first filtering result and the third table to obtain a second filtering result; then, setting a first association operation and a second association operation according to the first filtering result and the second filtering result to obtain a second logic execution plan; according to the method, the statements used for guiding the association operation in the logic execution plan can be optimized, so that the optimized logic execution plan can greatly reduce the amount of data needing to execute the association operation in the two tables in the subsequent implementation, and the execution efficiency of the data query request is improved.

One or more example embodiments also provide an electronic apparatus and a method of operating the same, which may improve efficiency of computing resources used for log processing (rule engine checking) by abbreviating / filtering duplicate logs when a large amount of log data is collected, and may minimize information that may be lost in a process of abbreviating and filtering log data, thereby preventing detection omission (erroneous detection).SOLUTION: The method includes extracting data for each item matched with a plurality of predetermined items from the log data, acquiring a hash value for each item by applying the extracted data for each item to a hash function matched with each item, checking whether the log data is duplicated based on whether the hash value for each item is duplicated, updating a duplication count according to the checked duplication, and detecting a threat based on the identified data for each item and the updated duplication count.SELECTED DRAWING: Figure 2

A system and method generate a dynamic and query adaptive Bloom filter for optimal joining of tables such as large tables in distributed data processing systems. A Bloom filter is dynamically constructed and tuned based on historical query patterns including frequency and selectivity. Metrics are collected from execution of an Adaptive Query Execution (AQE) based execution plan and execution of a Bloom filter-based execution plan generated from the constructed and tuned Bloom filter. A score measuring performance of the execution plans is generated from the metrics of each of the execution plans. The execution plan with a greater score is selected to optimally join the tables. The method implements the system.

The application discloses a data caching method and device, and relates to the technical field of computers. A specific implementation of the method comprises the following steps: listening to each node of a distributed scheduling center; wherein, a directory of the node is in one-to-one correspondence with each data table in each database, and node information saved by the node comprises a data change timestamp of the data table corresponding to the node; if it is found that the node information saved by the node has changed, generating a cache identifier and a Bloom filter according to the directory of the node and the changed node information; associating the cache identifier with the Bloom filter, and storing the cache identifier and the Bloom filter corresponding to the cache identifier into a filter set. The implementation can solve the technical problems of great development difficulty, uneven memory, blocked query or inconsistent data.

The application relates to a SkyWalking call link sampling method based on a computer software technology field.The method comprises the following steps: reporting link data in an agent end to a server end in full amount; forwarding the link data to a Kafka asynchronous consumption; judging the link needing sampling in a first round of consumption and recording a TraceId, writing the TraceId into a sampling Bloom filter, and storing the TraceId into a first storage unit in full amount; judging whether the TraceId exists in the sampling Bloom filter in a second round of delayed consumption, storing the TraceId into a second storage unit and writing the TraceId into a query Bloom filter if the TraceId exists; and routing to the corresponding storage unit according to the TraceId and the query Bloom filter during the query.The application solves the problems of incomplete sampling, inaccurate indexes, incomplete links, high storage cost and low query efficiency through full amount reporting, asynchronous decoupling, two rounds of consumption, double Bloom filters and storage separation.

The application realizes a Bloomfilter coding privacy protection reinforcement method based on ULDP through the method in the network security field, and comprises a reading module, a coding module and an output module.The reading module is used for reading the personal identification information data of patients in different hospitals and performing standardization; the coding module is used for coding the personal identification information so that the patient information is not exposed, and a data column mark with unified format is generated; and the output module outputs the encrypted patient data; and the coding module adopts a Utility-optimized Bloomfilter Flip method or a Utility-optimized Laplacenoise Addition method to realize the coding. The method provided by the application designs a scheme for realizing smaller privacy cost and better matching effect in the data coding privacy protection process of hospital patient information in the scene of coding and encryption of hospital patient information.

The application provides a data access method and an electronic device, and relates to the field of information security. The data access method extracts the latest N position information associated with a target event from the acquired trajectory information of a terminal device in a TEE. The terminal device performs hash calculation on a set Bloom filter in the TEE to obtain a first hash value, and signs the first hash value by using a private key, wherein the Bloom filter records each position information of the trajectory information. The terminal device sends an access request to a host. The terminal device receives data sent by the host after the access request is verified. The terminal device only needs to sign the first hash value by using the private key once, thereby improving the efficiency of signature and saving the computing resources on the basis of ensuring data security. When verifying the signature, the host only needs to verify the first hash value once, thereby improving the verification efficiency and saving the computing resources.

Disclosed herein are systems, methods, and technology for secure data dissemination in a network that reduces false positives. A method can include: initializing a bloom filter, generating a cryptographic seed value, generating salted data based on combinations of the cryptographic seed value and each data value in a set of local data values, injecting the salted data into the bloom filter to generate a salted bloom filter, selecting a random peer node in a network, transmitting the salted bloom filter and the cryptographic seed value to the selected random peer node, receiving, from the selected random peer node, at least one other data value that was identified by the selected random peer node as not being included in the salted bloom filter, and adding the at least one other data value to the set of local data values.

The embodiment of the invention provides a cloud file query method and related equipment, and belongs to the technical field of data query. The method comprises the steps of performing encryption processing on a first service pool and a first total pool through a preset encryption algorithm to obtain a corresponding second service pool and a second total pool; wherein the preset encryption algorithm comprises a reversible coding algorithm; constructing a preset bloom filter through a preset non-encrypted hash function according to the second total pool; comparing and analyzing the second business pool through the preset Bloom filter, and determining a target file identifier; wherein the target file identifier comprises a file identifier which exists in a second service pool and does not exist in a second full-amount pool; performing decryption processing on the target file identifier to obtain a target query result; wherein the decryption processing corresponds to the encryption processing. According to the embodiment of the invention, the efficiency and accuracy of master-free file checking can be effectively improved, and support is provided for performance optimization of cloud storage services.

This invention relates to the field of data retrieval technology, and in particular to a method, apparatus, medium, and device for retrieving target user data. By obtaining the number of aggregates corresponding to each aggregated data in the current level, the method acquires the number of aggregated data corresponding to each aggregated data in the next level and the number of aggregates corresponding to each aggregated data, thereby progressively constructing a multi-level aggregated data structure. A suitable target level identifier is determined through preset conditions to avoid over-segmentation or insufficient aggregation in the hierarchical structure, balancing data aggregation degree and retrieval efficiency. Then, the method progressively compares and searches downwards within the hierarchical structure to ultimately determine whether the target user data has been retrieved. This approach effectively utilizes the hierarchical structure to rationally organize massive amounts of data, improving retrieval accuracy, and leverages the characteristics of Bloom filters to achieve efficient data retrieval.