59 results about "Financial security" patented technology

The invention relates to the technical field of cloud computing financial security, and provides a financial data encryption transmission and storage method. The method is characterized by comprising the following steps of: executing sensitivity-driven data grading fragmentation on a user terminal; dynamic elliptic curve encryption is carried out on transmission data through a two-channel encryption engine, and fully homomorphic encryption is carried out on storage data; dynamically distributing the fragments to heterogeneous cloud nodes by the multi-cloud routing based on reinforcement learning; a distributed key management matrix is constructed, key fragments are dispersed and stored in a block chain and a hardware security module, and reconstruction is activated through biological characteristics. The method has the advantages that full-link ciphertext operation is realized, and the plaintext exposure risk is eliminated; ciphertext state financial calculation is supported; single point failure is resisted; the APT attack is defended dynamically; and the quantum security evolution capability is realized. The method is suitable for mobile banks, cross-border payment and other scenes.

The invention is suitable for the technical field of financial security, and provides a financial transaction real-time anti-fraud monitoring method and system, and the method comprises the steps: collecting user equipment interaction data in real time, extracting an operation curvature change spectrum feature vector, and recognizing a conventional verification step missing time period and an equipment silent state interval; calculating a local entropy speed increase rate and capital network temperature gradient space distribution, and generating an entropy change index; setting a curvature detection threshold value according to the entropy change index, executing multi-scale mode matching on the equipment silent state interval, and obtaining equipment peripheral signal data; performing space-time convolution fusion on the peripheral signal data and the pressure value sequence, and executing a pressure test; and carrying out space-time correlation analysis, identifying a multi-dimensional abnormal signal, and generating a cross-scale risk early warning instruction. Through multi-dimensional data fusion and dynamic risk assessment, the accuracy and scene adaptability of financial transaction real-time anti-fraud monitoring are improved, and an effective guarantee is provided for financial transaction security.

The invention discloses an anti-money laundering intelligent analysis system and method, and relates to the technical field of financial security, and the method comprises the steps: defining nodes and edges for a transaction subject and a fund flow direction based on an original transaction data set, and constructing a transaction relation graph; analyzing an abnormal region set of fund flow based on the transaction relation graph, identifying whether a hidden transaction mode exists in the abnormal region set, and extracting a suspicious transaction sub-graph; performing risk assessment on each node in the suspicious transaction subgraph by adopting a random forest algorithm, if a risk score is greater than a risk threshold, marking the node as a high-risk node, and generating a high-risk transaction path; the contextual information of a high-risk transaction path is extracted, feature vectorization processing is performed on the contextual information, a risk interpretation model is constructed, a risk interpretation report is generated, and a set of complete interpretable anti-money laundering risk control system is realized.

The invention provides a multi-factor biological recognition and behavior feature fusion identity verification method and system, and the method comprises the steps: responding to any financial user at the entrance position of a corresponding financial place, carrying out the height comparison of the financial user and an entrance door frame, and obtaining a comparison result; the financial user is endowed with a corresponding first attribute based on a comparison result; responding to any financial user with the first attribute facing the ATM equipment in the equipment interaction circle corresponding to any ATM equipment, and giving a corresponding second attribute to the financial user based on the obtained posture information corresponding to the financial user; in response to the fact that the financial data card is inserted into the ATM equipment and the first attribute and the second attribute corresponding to the financial user correspond to the juvenile attribute, identity information corresponding to the financial user is obtained, and information verification is conducted on the identity information on the basis of pre-stored verification information corresponding to the financial data card. The financial security is at least improved.

The invention discloses an account quotation management method and system based on account credible authentication. The method comprises the following steps: extracting account information from a data warehouse, extracting a credible factor, and constructing an account credible file; acquiring flow data of the account; performing account risk level evaluation according to the account credible file and the flow data to obtain an account risk level; determining a rating decision according to the account risk level to obtain a decision result; when the decision result is passing or manual service, the flow data is input to an account credibility rating model for credibility rating evaluation to obtain an account credibility rating; acquiring account related information; calculating the account quota according to the account credibility level and the account related information to obtain a calculation result; and outputting the account risk level and the calculation result. By implementing the method provided by the invention, more comprehensive, flexible and efficient risk control and limit management can be realized, various transaction and account risks can be better handled, and financial security and user experience are improved.

The invention provides a multi-dimensional anti-fraud and risk control auditing method and system for large-amount transactions, and relates to the technical field of financial security, and the method comprises the steps: segmenting historical data of two transaction parties to extract multi-dimensional features, decomposing a transaction amount sequence in combination with wavelet transform, and constructing a behavior probability distribution model; acquiring equipment environment data and calculating an equipment credit score; utilizing dynamic causal reasoning fusion to calculate an initial risk score; when the pre-warning threshold value is exceeded, generating a transaction verification problem and evaluating the risk by adopting a progressive active learning verification method; and finally determining a risk control strategy according to the risk score. According to the method, the large transaction risk identification accuracy is improved, and the error interception rate is reduced.

The invention discloses a self-supervised graph anomaly detection method based on global space correlation perception, and relates to the fields of financial security, network security and the like. The method comprises the following steps: sampling global and local sub-graphs based on graph diffusion and random walk; local and global information of coding is learned through double-view comparison; utilizing node attribute consistency characteristics based on attribute reconstruction learning; and training the contrast learning module and the reconstruction learning module in a combined manner and fusing scores to realize anomaly detection. According to the method, local and global structure information and node attribute features are integrated, so that the influence of graph neural network signal smoothing on anomaly detection is effectively relieved, the detection accuracy of abnormal nodes in an attribute network is improved, and the method is suitable for anomaly detection of scenes such as social networks and transaction networks.

Systems, methods, and computer program products for alerting a user of an anomaly concerning a publicly traded financial product, such as a publicly traded financial security with potentially upcoming volatility, include obtaining online chatter from one or more social media platforms associated with the publicly traded financial product posted over a first time interval, determining, at the end of the first time interval, an anomaly concerning the publicly traded financial product based at least in part on the online chatter associated with the publicly traded financial product, and responsive to determining the anomaly, providing an alert to the user. Determining the anomaly is based at least in part on historical data regarding online chatter associated with the publicly traded financial product from a prior time interval before the first time interval.

The invention provides a transaction platform security early warning method, system and device and a medium, belongs to the technical field of financial security, and is used for realizing safer security transaction full early warning. The method comprises: a security anchor receives an operation request message from a terminal, the operation request message instructing a client to request to execute a first operation, the first operation being a transaction operation or a security modification operation for a transaction, and the client being a client on the terminal corresponding to a transaction security platform; the security anchor triggers bidirectional authentication between the security anchor and the client in response to the client requesting to execute the first operation; information used in the bidirectional authentication is determined based on a long-term key of the terminal, and the long-term key is authorized to the transaction security platform by an operator to which the terminal belongs; and under the condition that the two-way authentication fails, the security anchor point determines that the security risk exists and refuses to execute the first operation.

The application belongs to the technical field of financial security, and discloses a cross-institutional fraud detection method based on federated graph learning and oriented to privacy protection, which comprises the following steps: each participant constructs a transaction graph according to the transaction text description of the included account, and performs enhancement processing on the transaction graph to obtain an enhanced subgraph; each participant iteratively trains a graph Transformer using the enhanced subgraph until a local training end condition is reached, and uploads local model parameters of the graph Transformer to a central server based on a differential privacy mechanism; the central server aggregates the local model parameters of all participants to obtain global model parameters, and distributes the global model parameters to each participant; the global model parameters serve as initial model parameters for local training of each participant, and the federated training is repeated until a federated training end condition is reached. The application is more robust to cross-institutional, heterogeneous and sparse sample scenarios, and can reduce false negatives and false positives.

The present application relates to the technical field of financial security, and particularly relates to a financial order security payment method and device, computer equipment and storage medium, login environment information, location information and binding vehicle information of a user are acquired, if it is detected that the login environment information meets a preset payment environment, a historical payment location is acquired, a first payment location range is determined, a second payment location range is determined according to the first payment location range and the historical payment location, if it is detected that the location information is within the second payment location range, the security payment of an order is completed. By acquiring the login environment information, the location information and the binding vehicle information, if the login environment information meets the preset payment environment, the location information is detected, if the location information meets the second payment location range, the binding vehicle information is detected, if the binding vehicle information meets the binding operation on the preset operation page, the order payment is completed. Thus, the payment risk is comprehensively and automatically detected, so that the payment of the financial order is safely completed.

The utility model relates to the technical field of money binding machines, and discloses a punching device of a money binding machine, which comprises a rack, a rotating shaft and a transmission rod which are rotatably and transversely arranged on the rack, a melting belt punching head arranged in front of the rotating shaft and the transmission rod, and a driving mechanism used for driving the transmission rod to rotate, the rotating shaft and the transmission rod are connected with the melting belt punching head through a connecting rod structure, so that the melting belt punching head can move up and down, the melting belt punching head comprises a seat body, a melting hole head and a heating pipe, a mounting hole penetrating from top to bottom is formed in the seat body, and the melting hole head is inserted into the mounting hole of the seat body from top to bottom and is locked through a locking structure. The top of the hole melting head is integrally provided with a heat conduction sleeve for insertion of the heating pipe. According to the punching device of the money binding machine, the design of the replaceable hole melting head is adopted, the mounting hole is formed in the base body, the hole melting head can be conveniently inserted and pulled out and fixed through the locking structure, and the anti-counterfeiting requirements of upgrading along with financial security requirements and diversification of different customer groups can be easily met.

The embodiment of the invention provides an enterprise group relationship determination method and device, equipment, a medium and a product. The method comprises the following steps: pre-calculating enterprises in a daily pre-calculation list, generating a stock equity tree of the enterprises, storing the stock equity tree in a data table, and obtaining relation data corresponding to the stock equity tree when determining that the stock equity tree of a target enterprise exists in the data table based on a query request of the target enterprise, calculating a maximum stockholder corresponding to the target enterprise and each corresponding leaf node enterprise, determining whether the stock equity tree of each leaf node enterprise is missing in the data table, and if yes, performing layer-by-layer stock equity penetration on the missing leaf node enterprise to obtain the stock equity tree of the corresponding leaf node enterprise, and determining and outputting the group relationship of the target enterprise according to the stock equity tree of each leaf node enterprise. The method is used for achieving the effects of improving the comprehensiveness and reliability of the enterprise group relationship, improving the accuracy and effectiveness of enterprise credit granting and enhancing the financial security of banks.

The utility model discloses a document collection box for economic and financial securities, which comprises a storage box, one end of the storage box is rotatably connected with a connecting plate, the other end of the connecting plate is connected with a fixing plate, and the fixing plate rotates through the connecting plate to open and close the document collection box; a plurality of bandages are fixedly arranged in a bottom plate of the storage box, a plurality of rotating shafts are arranged at the outer end of a fixing plate, and blocking rods are fixedly arranged on the outer walls of the rotating shafts and rotate through the rotating shafts to achieve the function of fixing or releasing the fixing function of the fixing plate and the storage box. According to the file storage box, the bandages for fixing stored files and the stop levers for fixing the fixing plates are additionally arranged, so that the effect that the files are fixed in the storage box and are not prone to falling out when the files are stored is achieved, and the problem that the files fall out of the storage box due to external force collision when the files are stored is solved; and the high efficiency of the document collection box for economic and financial securities is improved.

The invention discloses an abnormal terminal device identification method and apparatus, and an electronic device. Relates to the field of financial security. The method comprises the following steps: acquiring multi-modal feature data of target equipment; the multi-modal feature data are input into M target clustering models respectively, M clustering results are obtained through processing, and each clustering result comprises a numerical value under a risk factor; and determining a risk score of the target device by using the M clustering results, determining a risk level represented by the risk score according to the risk threshold interval, and determining an abnormal state of the target device according to the risk level. According to the method and the device, the problem of relatively low identification accuracy of identifying the risk equipment by using the static identification information in related technologies is solved.

The invention discloses a system and method for ensuring security of an electronic transaction platform, and relates to the technical field of financial security, and the method comprises the steps: capturing the dynamic change information of an optical flow field in a current transaction terminal environment in real time, and generating optical flow field gradient data through the frame-by-frame analysis of the gradient change of illumination intensity in space and time; when the electronic transaction risk probability value exceeds a preset probability threshold value, continuously observing the time sequence fluctuation of the gradient data of the optical flow field at a dynamic frequency, performing high-frequency measurement on a forced attack transaction process to enter a quantum sesame effect freezing state, and outputting a freezing signal; triggering a transaction freezing instruction with a time lock based on the freezing signal, and generating a transaction freezing event; and the transaction freezing event is encrypted and written into a distributed account book to generate a judicial audit evidence chain, and the security disposal of the electronic transaction is completed. According to the invention, through a dynamic frequency quantum observation mechanism, when the risk probability exceeds the threshold value, the gradient time sequence fluctuation of the optical flow field is measured at high frequency, so that the attack process enters a quantum sesame frozen state.

1. Name of the product in this design: U-Shield. 2. Purpose of this design: Primarily used in the field of electronic payment, providing electronic keys to ensure financial security. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

This application provides a smart management device for a financial USB key based on dynamic encryption, relating to the field of financial security equipment technology. It includes: a USB key body; an interface disposed at one end of the USB key body; a recess disposed on the interface; and a sliding cover containing an inner cavity, slidably disposed on the USB key body and covering the interface through the inner cavity. This application achieves both dynamic protection and stable insertion of the interface through the synergistic action of the sliding cover and an elastic element. When the device housing abuts against the sliding cover, it drives the elastic element into a semi-rigid state, pulling the rolling shaft to deform the spring sheet, forming a compression protrusion inside the device, making it difficult for the USB key to accidentally dislodge and ensuring a stable connection. When the sliding cover is closed, the structural characteristics of the elastic element enhance its sealing effect.

A method, apparatus and system are disclosed for providing a user with an indication of the user's financial security level. In order to achieve this, the user may be surveyed to provide information related to the user's attributes and current level of financial security. Based on the user's inputs, a financial security tool may generate a financial security score and monetary risk amount that provides an accurate interpretation of the user's financial security level.

The invention provides a financial fraud early warning identification method and device, a storage medium and electronic equipment, and is applied to the technical field of financial security. According to the method, the to-be-recognized pipeline information is obtained and input into the fraud early warning recognition model combining the particle swarm optimization algorithm and the gradient boosting decision tree algorithm, and the fraud probability value is obtained from the fraud early warning recognition model. And if the probability value exceeds a preset allowable threshold value, further performing full-amount matching on the pipeline information and an early warning rule base so as to trigger corresponding fraud early warning. According to the method, a fraud early warning identification model combining a particle swarm optimization algorithm and a gradient boosting decision tree algorithm is used, a fraud probability value corresponding to a pipeline can be quickly obtained, so that quick screening of a huge data volume is realized, and whether full-volume rule matching needs to be performed or not is quickly judged by setting a fraud allowable probability threshold value; and the early warning can be efficiently triggered in a complex fraud scene.

The invention provides a money laundering risk analysis device and system, and relates to the technical field of financial security. In the application, a rule configuration module is used for generating a first review rule and a second review rule based on a rule configuration operation of business personnel for money laundering risk analysis business; the first review module is used for performing compliance review on the identity information of the reviewed person based on a first review rule to obtain a compliance review result of the reviewed person; the second review module is used for performing transaction risk review on the transaction information of the reviewed person based on a second review rule when the compliance review result represents that the identity information meets the compliance condition, and obtaining a multi-dimensional feature radar map of the reviewed person; and the risk analysis module is used for determining a money laundering risk analysis result of the examined person based on the multi-dimensional feature radar map and a preset money laundering risk community. Therefore, the dependence of money laundering risk analysis on manpower is reduced, and the efficiency of money laundering risk analysis is improved.

The invention discloses a process management method and device of a financial host, electronic equipment and a storage medium. The method comprises the following steps: establishing an information asset data lake corresponding to a target financial center; collecting process dynamic characteristics of a financial host in the target financial center based on the information asset data lake; generating a service fingerprint according to the process dynamic characteristics, and determining a three-level responsibility matrix according to the service fingerprint; and performing process management on the financial host based on the three-level responsibility matrix and the service fingerprint. Based on the technical scheme, the process dynamic characteristics of the financial host are collected, the corresponding service fingerprint is generated, the responsibility matrix is determined according to the service fingerprint, and process management is realized according to the responsibility matrix, so that the financial security defense line is enhanced, account-reality conformity of information asset management is realized, and the supervision efficiency is improved.

The invention discloses a bar code payment method and system for multiple payment institutions, and relates to the technical field of quantum financial security, and the method comprises the steps: collecting gravitational field data, calculating a four-dimensional space-time coordinate of a user through a Carrousel-Claien five-dimensional field equation, triggering the plasma resonance wavelength locking of an SPP metamaterial layer, and building an optical enhancement field; performing quantum entanglement photon pair scanning by using an optical enhancement field, decoding a payment institution routing parameter set through a Bell inequality violation value, and generating a non-localized quantum signature; performing Riemannian manifold curvature matching on the four-dimensional space-time coordinate and a geographical fence boundary of the payment institution, and when the four-dimensional space-time coordinate is within a fence boundary threshold, triggering a target payment institution screening instruction and binding a non-localized quantum signature; according to the method, the four-dimensional space-time coordinates of the user are calculated by collecting the gravitational field data and applying the Carrouba-Claien five-dimensional field equation, so that high-precision space-time positioning and photon regulation are realized.

The invention relates to a risk control method and system for financial security, and aims to solve the problems of detection lag, data islands, poor model adaptability and the like in a traditional risk control system. Structured and unstructured data are collected in real time from multi-source financial data, and a standardized data set is generated through preprocessing; constructing a high-dimensional feature vector containing a user behavior sequence, fund network features and text emotion features by using a distributed computing framework; training and risk assessment are carried out by adopting an integrated model fusing an isolated forest, a gradient boosting decision tree and a deep neural network; real-time transaction decision making and interception are realized in combination with a dynamic threshold strategy driven by reinforcement learning; and a federated learning framework is introduced to realize multi-party security joint modeling on the premise of ensuring data privacy. According to the method, the functions of real-time complex event processing, incremental learning optimization and interpretability analysis are integrated, a closed-loop risk control system is formed, and the recognition capability, the adaptability and the decision transparency of a novel fraud mode are remarkably improved.

This invention discloses a customer identification and dynamic monitoring analysis system and method based on intelligent agents, belonging to the field of big data monitoring technology. The invention identifies structured transaction data in target customer transfer requests and assigns an independent code to each customer; it then filters out suspected risk data based on a first risk assessment condition; it calculates the correlation between suspected risk data and transaction data by weighting the correlation based on transfer time correlation, co-occurrence correlation, and interval correlation; and it distinguishes between risky and non-risky data based on a second risk assessment condition. Simultaneously, it sets an optimization cycle, adjusting the weights in the correlation calculation according to the risky data and the first risk assessment condition. This method can reduce false triggering rates, decrease manual and computational costs, dynamically adapt to risk characteristics, improve the timeliness of risk interception and the comprehensiveness of illegal transaction identification, and safeguard financial security.

This invention belongs to the field of intelligent monitoring technology for financial security, specifically involving an anomaly detection system and method for self-service financial service terminals and vault security facilities. The system includes: (1) a sensing end; (2) an edge processing layer; and (3) a central management layer. The method includes: S1, data acquisition and synchronization; S2, multimodal feature extraction; S3, dual-channel fusion and judgment; S4, rule engine enhancement and final output; and S5, alarm generation and intelligent linkage response. This invention achieves accurate identification of abnormal states, low false alarm reporting, and intelligent linkage response through spatiotemporal alignment, multi-level feature fusion, and rule-AI collaborative decision-making, thereby significantly improving the security protection level and automated management capabilities of financial physical facilities.

The invention relates to the technical field of security evaluation of digital asset accounts, in particular to a digital asset account security report generation method based on a large language model. The method comprises a training process and a reasoning process, wherein the training process comprises report collection and cleaning (redundancy removal and core field extraction), structured processing, transaction data acquisition preprocessing (comprising structured fields and derivative features), subgraph construction enhancement (comprising time sequence slicing and feature definition), semantic extraction, corpus construction and model fine tuning; the reasoning process comprises demand acquisition, real-time data acquisition, sub-graph construction, semantic extraction and report generation post-processing, and semantic understanding is deeply integrated in combination with graph neural network structure learning and large language model semantic analysis capability to capture fine-grained features. According to the method, account transaction spatio-temporal characteristics and semantic information can be comprehensively captured, evaluation accuracy, real-time performance and interpretability are improved, a report meeting financial risk control requirements is generated, and the practical application value in the financial security field is enhanced.

The present application relates to the field of financial security and biometric identification, in particular to a bank user identity verification method and system based on image recognition, comprising: obtaining a user's facial dynamic video and high-resolution iris image through a terminal; performing live detection and micro-expression analysis on the facial video to extract facial activity features, and performing texture enhancement and feature point positioning on the iris to extract iris structure features; fusing the two to generate an on-site biometric feature template, and comparing the template with a pre-stored registration template to generate a matching degree matrix; combining real-time transaction behavior and historical patterns to weight and calibrate the matching degree matrix, obtaining a calibrated score; determining the identity authenticity according to the comparison result of the calibrated score and the dynamic security threshold, and controlling account access and recording logs accordingly. The method enhances the anti-counterfeiting capability of live detection by analyzing micro-expression, and improves the adaptive security of identity verification for different risk scenarios through behavior context dynamic calibration.

The invention discloses a public opinion risk control method and a related product. The method comprises the following steps: acquiring a public opinion service task of a tenant; splitting the public opinion service task according to a service scene to obtain a plurality of scene tasks; determining a service scene model corresponding to each scene task, and constructing a plurality of objective functions based on the plurality of service scene models and the plurality of scene tasks; performing optimization solution on the plurality of target functions to obtain an optimal solution corresponding to each target function; combining the optimal solutions corresponding to the multiple objective functions, and determining a service combination corresponding to the public opinion service task; and public opinion risk control is carried out on the public opinion service task based on the service combination, thereby solving the problems of low efficiency of traditional risk control and difficulty in timely identification of risk transactions. According to the method, the unreasonable world financial information order is broken through, the national information security and financial security are guaranteed, the risk control accuracy and response speed are improved through the characteristics of multi-source data support and real-time dynamic optimization, and the high-quality development requirement of the financial field is comprehensively met.

The invention discloses an encrypted financial abnormal behavior detection method and system based on an isolated forest, and belongs to the technical field of financial security. The method comprises the following steps: acquiring financial transaction data of a payment terminal and extracting a feature vector; encrypting the feature vector by adopting a homomorphic encryption algorithm to generate a ciphertext feature vector; performing secret state reasoning on the ciphertext feature vector based on an isolated forest model, and calculating a path depth ciphertext of each sample in the financial transaction data through a lookup table and a homomorphic encrypted MUX gate; and integrating the path depth ciphertext and decrypting to obtain an abnormal score, and judging whether the financial transaction data is abnormal or not according to a scoring result. According to the method, efficient anomaly detection of the financial data in the encryption state is realized, the privacy security of the whole flow of the data is ensured, and meanwhile, the detection efficiency is remarkably improved by optimizing ciphertext calculation logic. The method is suitable for scenes of online payment risk control, fraud prevention and the like, and has high security, high real-time performance and strong expansibility.