74 results about "Candidate key" patented technology

The invention discloses a semantic auxiliary vision SLAM loopback detection method based on topological graph matching, and belongs to the field of computer vision. The implementation method comprises the following steps of: screening out candidate key frames without a common-view relationship by judging whether the common-view relationship exists between a current frame and each frame in a historical key frame sequence or not; and constructing a semantic topological graph, namely constructing nodes and undirected weighted edges in the topological graph and calculating node descriptors, and realizing topological expression of the key frame image by constructing the semantic topological graph and calculating a feature descriptor for each node in the topological graph. And calculating an affinity matrix, constructing the affinity matrix between the topological graphs by combining the similarity between the weights of the node descriptors and the edges in the topological graph of the current key frame and the topological graph of the candidate key frame, and calculating an incidence matrix between the nodes of the topological graphs at the same time. And calculating the topological graph similarity through the affinity matrix and the incidence matrix. And judging whether loopback detection succeeds or not by judging whether the topological graph similarity reaches a loopback detection threshold value or not.

The invention provides an optimization method, device and equipment for a quantum key distribution handshake protocol, and the method comprises the steps: preparing a standard quantum state and building a spinning peak shifting time sequence, and achieving the time division multiplexing and parallel processing of a plurality of quantum channels; constructing a handshake mode with successful pre-matched codebook storage history, and supporting rapid mode matching; the authentication sub-process and the negotiation sub-process are decoupled through a parallel verification architecture and are executed in parallel on different time phases; the quantum signature token and the key negotiation parameters are fused to generate a handshake state matrix, and global representation of the handshake process is achieved; performing success probability pre-judgment based on quantum entanglement association strength analysis, and triggering a pre-generation mechanism of a candidate key pool; performing quantum state weaving and fusion on the key by using local, non-local and mixed entanglement distribution adjustment to generate an enhanced key; and finally, optimal distribution is completed in combination with a spinning peak shifting time sequence, so that parallelization of authentication and negotiation, intellectualization of resource distribution and real-time state monitoring are realized.

The invention provides a key point path planning method and device based on distance transformation, and the method comprises the steps: converting a grid map of a target region into a distance transformation map based on a distance definition method; a distance maximum value point is extracted from the distance transformation map to serve as a candidate key point, the candidate key point is screened to obtain a global key point, and at least two contact points exist between a circle generated with the global key point as the circle center and the distance value of the global key point as the radius and a grid representing a non-passing area; and constructing a connection relationship between the global key points, and searching and determining a navigation path based on the connection relationship between the global key points by using a # imgabs0 # algorithm. According to the method, the global key points are screened in the distance conversion map, and path search is performed based on the connection relation between the global key points, so that a more efficient robot path planning algorithm is realized.

The invention discloses a key management method and a storage device, and belongs to the field of storage security, the method comprises the following steps: deriving different types of key fragments from an authentication key according to different preset classification strategies, and respectively storing the different types of key fragments in different storage partitions corresponding to the preset classification strategies; receiving a data access request, wherein the data access request comprises data index information; based on different preset classification strategies, reading candidate key fragments matched with the data index information from the different storage partitions respectively, verifying the legality of the candidate key fragments matched with the data index information, and determining the candidate key fragments passing the verification as effective key fragments; and aggregating the effective key fragments of different types to generate the authentication key, and obtaining target access data of the data access request through the authentication key. According to the invention, the security of key storage and the flexibility of key management can be effectively improved.

The invention provides a point cloud key point generation method based on a key point detection network and a descriptor network, and the method comprises the steps: carrying out the random sampling of the key point detection network, obtaining candidate key points, carrying out the multi-level clustering with each candidate point as a center, expanding a sensing domain, and aggregating the neighborhood information, aggregated information is sent to a double-head attention mechanism to calculate a neighborhood point weight, and more representative key points are selected; the descriptor network receives the attention feature map of the detection network, carries out fusion learning on global information and local information of each key point, and calculates a descriptor and a direction vector for each key point. Secondary screening of the key points is carried out while the descriptors are optimized by using a joint matching loss function, and the key points with strong characteristic characterization force are obtained. Compared with the prior art, the time consumption is shortened by 90%, the key point repetition rate is 70%, the matching precision is 90% or above, and good robustness is achieved under different Gaussian noises.

A system and method for extracting structured key information from diverse document types using large multimodal models (LMMs) is disclosed. The invention employs a zero-shot analysis to identify candidate keys within an input document, then selects a document schema from a document schema database based on the identified keys. The LMM is prompted with the selected document schema to generate structured key-value pairs, with field constraints enforced by the document schema. Relationships among extracted keys are mapped to a graph representation, enabling robust handling of complex document layouts. The system supports nested structures, tabular data, and alias definitions for fields, and can update document schemas based on ground truth feedback. The resulting structured output is provided in a machine-readable format, enabling reliable and scalable document understanding across varied domains such as invoices, health cards, and driving licenses.

The invention belongs to an infringement recognition method, and provides a three-dimensional model block chain copyright infringement recognition method, system and program product for solving the problems that an existing three-dimensional digital copyright infringement recognition method is low in recognition accuracy, poor in recognition effect in a complex scene and not applicable in a high-precision requirement scene. And calculating the Hamming distance between the copyright fingerprint set of the three-dimensional model to be detected and the copyright fingerprint set of the three-dimensional model registered on the given chain, and judging whether to infringer according to the relationship between the Hamming distance and a preset overall matching rate threshold. Wherein during copyright fingerprint set calculation, key point scales in all vertexes of a three-dimensional model are determined according to the geometric volume and surface complexity of the three-dimensional model, mixed feature descriptors are obtained by combining geometric structures and surface texture changes of local neighborhoods of candidate key points, and corresponding fingerprint abstract values are calculated after Hash processing. And the recognition stability under non-infringement operations such as rotation, zooming, slight editing and the like is remarkably improved.

A kind of frame extraction method for road test vehicle image information, comprising: obtaining road test vehicle image information, and marking candidate key frame in road test vehicle image information;According to the marked candidate key frame, based on actual demand, relevant threshold setting and index calculation;According to the set threshold and calculated index, key frame is marked;According to the marked key frame and set threshold and calculated index, similar frame is marked;According to neural network model, no key target frame is marked;According to the marked key frame, similar frame and no key target frame, image information is frame extracted.The present application is highly adaptable to the business scene of automatic driving, and can more effectively solve the data redundancy problem of storage end.Free limited human resources, and then improve the execution efficiency of the entire automatic driving tool chain.And different content section image scene is processed by divide and conquer, and the frame extraction result is more reliable.

In some implementations, a device may obtain a data set that indicates scores for first terms based on association scores between the first terms and second terms. The association scores may be based on occurrences of the first terms in electronic documents that provide transcripts relating to telecommunication interactions, and occurrences of the second terms in electronic records that provide summaries relating to the telecommunication interactions. The device may process an electronic document, that provides a transcript relating to a new telecommunication interaction involving an agent device and a user device, to extract candidate key phrases from the transcript. The device may determine a relevance score for each candidate key phrase based on the score(s), of the data set, associated with the first term(s) in the candidate key phrase. The device may generate tag(s) for the new telecommunication interaction based candidate key phrase(s) associated with highest relevance score(s).

The disclosed embodiments disclose a data processing method, apparatus, electronic device, and computer storage medium. The method comprises: obtaining side channel information collected from a cryptographic device; the side channel information is physical information leaked during the operation process in which the private key to be cracked participates when the cryptographic device performs a bilinear pairing operation; selecting target information from the side channel information; the target information is the side channel information corresponding to the private key to be cracked during the process of being moved; matching the target information with preset information templates corresponding to multiple candidate keys; the preset information templates include reference information corresponding to the candidate keys; and determining one of the multiple candidate keys as the cracked private key based on the matching result. This technical solution can crack a private key based on the characteristic that the operation process in which the private key participates is prone to information leakage during the initial relocation of the private key, thereby improving the success rate of the attack.

This invention provides an optimization method, apparatus, and device for a quantum key distribution handshake protocol. By preparing standard quantum states and establishing a spin-staggered timing sequence, time-division multiplexing and parallel processing of multiple quantum channels are achieved. A pre-matched codebook stores historically successful handshake patterns, supporting fast pattern matching. The authentication and negotiation sub-processes are decoupled through a parallel verification architecture, allowing them to execute in parallel at different time phases. A handshake state matrix is ​​generated by fusing quantum signature tokens and key negotiation parameters, achieving a global representation of the handshake process. Success probability prediction is performed based on quantum entanglement correlation strength analysis, triggering a pre-generation mechanism for the candidate key pool. Quantum state weaving and fusion of keys are adjusted using local, non-local, and mixed entanglement distributions to generate enhanced keys. Finally, optimized distribution is completed by combining the spin-staggered timing sequence, achieving parallelization of authentication and negotiation, intelligent resource allocation, and real-time state monitoring.

The present disclosure provides an information query method, device, equipment, storage medium and program product, relates to the technical field of data processing and computer, and particularly relates to the technical field of big data and intelligent search. The specific implementation scheme of the information query method is as follows: determining at least one candidate key information matched with the query information according to the query information; determining a first evaluation value for evaluating the candidate key information according to a key information evaluation parameter; determining at least one target key information from the at least one candidate key information according to the first evaluation value; and determining target content information according to the at least one target key information.

A stream processing method includes: obtaining a candidate generation sketch including k blocks; obtaining a verification sketch including k´ blocks; receiving records in a stream with insertions and / or retractions, each of the records including a key and a count that are in correspondence; updating the sketches by transferring each record to one of the k blocks of the candidate generation sketch and one of the k´ blocks of the verification sketch; querying the k blocks of the candidate generation sketch to determine a set of candidate keys; dividing the set of candidate keys into k´ sub-sets of candidate keys; testing each sub-set of candidate keys by using one of the k´ blocks of the verification sketch to obtain a verified current list of frequent keys; and outputting a current list of frequent keys in the insertion stream and / or retraction stream.

The invention proposes a method for constructing an original text reference library based on improved reinforcement learning, and the method comprises the steps: constructing a data set, carrying out the optimization of an online learning large model through combining with an online learning gradient updating strategy, and obtaining an optimized online learning large model; constructing a reference library based on a multi-layer index architecture according to an output result of the optimized LLM large model; for the optimized LLM large model, outputting a result, namely a plurality of candidate key expression statements, inputting the title, the text content and the corresponding candidate key expression statements into an auditing system, and performing manual auditing; inputting a to-be-verified article into the optimized online learning large model, outputting all candidate key expression sentences, and constructing a candidate expression sentence list; a structured phrase set and a sentence pattern structure regular expression formula are obtained from the candidate expression sentence list through a text analysis module, and phrase features are extracted through the structured phrase set; and performing retrieval in the reference library based on the multi-layer index architecture, and outputting a reference position and a similarity score.

The invention relates to a network protocol reverse analysis method, which comprises the following steps of: firstly, for each message in target network interaction flow, determining each global candidate key field position through numerical conversion and keyword position label analysis; then applying probabilistic reasoning and combining loop iteration to obtain the position of each target key field; and finally, obtaining a numerical vector corresponding to each message in the target network interaction flow, alternately optimizing and training by using an auto-encoder and a clustering algorithm, and analyzing each message under each cluster in a network protocol format. According to the design scheme, the problem of reverse analysis of the network protocol is effectively solved, keyword recognition is creatively constructed into a probabilistic reasoning problem, and the defect of uncertainty processing of a traditional method is overcome, so that a more accurate message format is output, and an efficient and comprehensive solution is provided for reverse analysis engineering of the network protocol.

The invention relates to the technical field of side channel analysis, and particularly provides a side channel analysis method and system based on bit decoupling and a medium, and the method comprises the steps: obtaining power consumption data during encryption, calculating an intermediate value, and carrying out the multi-label decoupling; extracting multi-scale features from the preprocessed energy traces, performing weighted fusion, and outputting global shared features; mapping the global shared features into initial bit features through linear projection, calculating a dependency relationship between the bit features by using an attention mechanism, and generating interactive bit features; the fusion proportion is dynamically adjusted through gating parameters, fusion features are input into a multi-label classifier, the posterior probability of each bit is obtained, and a loss function is adopted for training; and inputting a to-be-measured energy trace into the trained neural network model, outputting a prediction probability, and selecting a target key by calculating the confidence coefficient of the candidate key through traversal. According to the method, the quantity of required energy traces is greatly reduced, and meanwhile, the attack success rate in a low signal-to-noise ratio environment is remarkably improved.

The present disclosure relates to a key management method, device, storage medium and chip, and relates to the technical field of communication encryption. The key management method comprises: in the case that a local device exists an original key for communicating with a peer device, determining a first candidate key meeting a first target device trust level from the original key, and authenticating the first candidate key; in the case that the first candidate key passes the authentication, determining the first candidate key as a target key for the local device and the peer device to communicate, wherein the first target device trust level is a current device trust level of the local device and the peer device, so that the selected target key can meet the current device trust level, and in the case that the first candidate key passes the authentication, it is determined that the first candidate key can be directly used by both sides, so that the communication security is ensured while the communication response speed is accelerated.

The application discloses a search processing method and device, equipment and a storage medium, and relates to the technical field of intelligent search. The specific implementation scheme is as follows: obtaining a query word input by a user; determining at least one candidate key word matched with the query word based on a pre-established index relationship; the index relationship is an index relationship between the segmentation of part of the key words corresponding to each category obtained through clustering according to semantics and the corresponding key words; determining the relevance of each candidate key word and the query word, and screening the candidate key words that meet a set condition; and determining a target key word matched with the query word based on the screened candidate key words. Through the introduction and use of the index relationship between the segmentation of part of the key words of each category after clustering and the corresponding key words, the search time is reduced, the search efficiency is improved, and the recall ability of the search system is improved.

The present application relates to the technical field of vehicle identity authentication, and discloses a vehicle distributed identity authentication method and system based on biological characteristics, which comprises the following steps: a user completes initial biological characteristic registration on a source vehicle, and biological characteristics are bound with random keys by a fuzzy binding algorithm to generate a binding factor and a biological characteristic hash value and store them in association; when the user uses a target vehicle, the target vehicle locates the source vehicle according to the user identity and requests verification. The source vehicle sends the binding factor and the biological characteristic hash value to the target vehicle; the target vehicle collects the current biological characteristics of the user, recovers the candidate key by decoding operation using the binding factor, and generates a temporary biological characteristic hash value; and the authentication is completed by comparing the temporary biological characteristic hash value with the received biological characteristic hash value. The method uses a decentralized hash transmission and fuzzy binding verification mechanism to realize efficient, safe and non-repeated cross-vehicle identity authentication on the premise of protecting the privacy of biological characteristics.

The embodiment of the present application provides an event auditing method and device in a cloud environment, the method comprises the following steps: obtaining an event to be audited in the cloud environment; judging whether the event to be audited is a future key event according to candidate key event information, wherein the candidate key event information comprises a plurality of candidate key events and an association relationship between the candidate key events; in the case that the event to be audited is a future key event, judging whether the event to be audited is a dangerous event according to event parameter information of the event to be audited and preset event parameter information; in the case that it is judged that the event to be audited is a dangerous event, executing a first safety measure corresponding to the dangerous event.

This specification discloses a data connection method, apparatus, storage medium, and electronic device. In the data connection method provided in this specification, a semi-join query statement is received, the first data table and the second data table connected by the semi-join query statement are obtained, and the join condition in the semi-join query statement is determined; when there is a non-equality condition in the join condition, the second data table is grouped according to the join condition; according to the join condition, the non-equality candidate keys included in the non-equality condition for joining in the second data table are determined; for each group of data, according to the non-equality condition and the values of the non-equality candidate keys of each row of data in this group of data, a specified key value is determined, and the data of the row where the specified key value is located is determined as the specified row data; according to the specified row data in each group of data, a deduplicated second data table is constructed; the connection method between the first data table and the deduplicated second data table is modified to an inner join to obtain a query result.

The application discloses a key management method and a storage device, and belongs to the field of storage security. The method comprises the following steps: deriving different types of key fragments from an authentication key according to different preset classification strategies, and storing the different types of key fragments in different storage partitions corresponding to the preset classification strategies; receiving a data access request, wherein the data access request comprises data index information; reading and verifying the legitimacy of candidate key fragments matched with the data index information from the different storage partitions based on different preset classification strategies, and determining the candidate key fragments passing the verification as valid key fragments; and aggregating the different types of valid key fragments to generate the authentication key, and obtaining target access data of the data access request through the authentication key. The application can effectively improve the security of key storage and the flexibility of key management.

This invention provides a hierarchical tree-structured attention routing method, apparatus, and device for ultra-long contexts. The key-value (KV) cache is partitioned into devices based on token positions and equipped with local Q-index subtrees. Each device searches its local subtree from the root, layer by layer, to obtain a local candidate key position index set. Simultaneously, the query vector is input into the Q-routing tree to select paths layer by layer, obtaining the activated attention expert set, memory expert set, and FFN expert set. Then, each device's attention expert and memory expert performs calculations only within the range corresponding to the local candidate key position index set and obtains local outputs. Finally, a Q-communication tree aligned with the device's physical topology performs a step-by-step tree-structured reduction of each device's local outputs and merges them with the local FFN outputs to obtain the layer output. Thus, the three stages of KV retrieval, expert routing, and cross-device reduction all converge to the logarithmic level through the tree structure, thereby achieving collaborative dimensionality reduction.

The application provides a video reasoning segmentation method and device based on reinforcement learning visual fine-tuning, and relates to the technical field of image processing. The method comprises the following steps: obtaining candidate key frames and video description text based on input text and a video to be segmented; inputting the input text, the candidate key frames and the video description text into a first-stage model to obtain an evaluation result of the candidate key frames; based on the evaluation result, retaining or updating the candidate key frames to obtain selected key frames; inputting the selected key frames, the video description text and the input text into a second-stage model to obtain positioning information of a target object in the selected key frames; and determining a segmentation result of the target object in multiple frames of the video to be segmented based on the positioning information of the target object in the selected key frames. The first-stage model and the second-stage model are obtained by training a pre-trained multi-modal large language model using reinforcement learning. The application can improve the accuracy of the video reasoning segmentation result.

The invention relates to the technical field of security evaluation of encryption algorithms, and provides a virtual shuffling security analysis method and system for bit slice misuse, and the method comprises the steps: creating a counter array which comprises a plurality of elements, and the index of each element corresponds to the value of a candidate key; for virtual shuffling, collecting a plurality of groups of tracks, screening out effective tracks for each track group, and if the number of the effective tracks is smaller than a threshold value, discarding the track group; performing LDA operation on the reserved track group to obtain a recommended key set, and for each candidate key in the recommended key set, adding one to the value of the index position of the corresponding counter array; and after all the track groups are processed, traversing the counter array, finding out the key with the highest count as a correct key, counting the count of the correct key, and obtaining the actual recommendation frequency of the correct key. And the risk of misuse of bit slice virtual shuffling in IF-ELSE implementation can be efficiently identified.

Provided is a data structure information generation device for generating, by using a large-scale language model for processing according to a prompt, data structure information in which pieces of position information about keys and values included in a table portion of data described in a table format is designated in a text format. The device comprises: an input reception unit for receiving an input of the table portion of the data described in the table format; a proposal unit for proposing, to an operator, candidates of the keys and the values analyzed from the table portion; an instruction reception unit for receiving, from the operator, an instruction for correcting or confirming the candidates of the keys and the values; a range designation reception unit for receiving, from the operator, designation of a range of the table portion in the data described in the table format; a data structure information generation unit for generating the data structure information on the basis of the confirmed keys and values and the designation of the range of the table portion; and a presentation unit for presenting the generated data structure information to the operator.

The application provides a data query method and device, computer equipment and a storage medium. In the method, a data holder splices second holder key data obtained by performing privacy intersection calculation on data items corresponding to candidate key values, and then encrypts the second holder key data by using first holder key data obtained by performing privacy intersection calculation, and sends the encrypted data to a data query party. The data query party calculates first query party key data by using key reference data obtained by performing privacy intersection calculation and a query key value, and decrypts the encrypted data by using the first query party key data, and then obtains corresponding second query party key data based on the first query party key data, so as to determine to-be-queried data items from the decrypted data by using the second query party key data. Only encrypted data is transmitted between the data holding equipment and the data query equipment, and no specific plaintext data is involved, so that the data security of both parties is protected.

The invention discloses a contract information identification method and a related product. The method comprises the following steps: acquiring a contract text and a metadata template; the metadata template comprises a plurality of texts to be retrieved; if the text word number of the contract text is greater than a preset threshold value, constructing a temporary vector knowledge base based on the contract text; performing semantic filling matching on the plurality of to-be-retrieved texts in the metadata template to obtain a filled metadata template; matching the filled metadata template with a temporary vector knowledge base to obtain a candidate key set; the candidate key set comprises a matching result of each to-be-retrieved text; the matching result at least comprises a candidate value; and verifying the candidate key set to obtain a contract information identification result. According to the method, while the capability of processing long documents is guaranteed, the extraction precision and robustness of key information in complex and non-standardized contract terms are remarkably improved, and then the accuracy of contract information identification is improved.

Embodiments of the present application relate to a positioning method and device of a mobile device, an electronic device and a storage medium. A key frame is acquired by a vision camera installed on the mobile device; mapping information and a feature descriptor of the key frame are determined; a bag-of-words model and a key frame image database are obtained according to the feature descriptor of the key frame; a current image frame is acquired, and the current image frame is converted into a current frame bag-of-words vector based on the bag-of-words model; a candidate key frame with the highest matching score with the current image frame is determined from the key frame image database according to the current frame bag-of-words vector, and a target key frame is determined according to the candidate key frame; a target node index corresponding to the target key frame is determined according to the mapping information, and pose information of the mobile device is calculated according to the target node index, so as to position the mobile device; that is, the prior pose of the mobile device is provided by the bag-of-words model, and the positioning accuracy is improved.

The application relates to a method for detecting that ARADI password resists impossible statistical fault analysis, first, generating a plaintext to be processed at random, taking the plaintext as an input of an ARADI algorithm, introducing a random 4-bit fault in the second last round, and outputting a fault ciphertext. By enumerating subkeys of the last three rounds and impossible relationship analysis, false candidate key bits are excluded in advance, and an intermediate state is calculated. By using a statistical method, the hamming weight of the intermediate state is calculated, and the correct value of corresponding subkey bits is obtained. The fault introduction and analysis process are repeated, and finally all bit positions of the correct subkey of the last three rounds can be deduced, and the correct master key is deduced according to a key arrangement scheme of the algorithm. The method provided by the application is easy to implement, fast and high in accuracy, and provides an important analysis basis for security research on the ARADI password algorithm.