60 results about "Transaction time" patented technology

The invention provides a real-time fraud detection method and system based on multi-modal fusion, and belongs to the technical field of financial transaction fraud detection.The method comprises the steps that firstly, payment behaviors, transaction texts and account behavior data are connected in series through a transaction event unique identifier, and a real-time multi-modal transaction data link is formed; generating an inter-modal fraud association link based on the inter-modal fraud association link; performing interactive operation to obtain cross-modal fraud intermediate features; constructing a transaction fraud tendency path according to a transaction link time sequence; and finally, analyzing the transaction fraud tendency path to determine a fraud association level, generating a fraud response instruction containing a transaction blocking instruction and risk notification content, and transmitting the fraud response instruction to a transaction processing system to terminate the transaction, so that multi-modal data can be comprehensively integrated, a transaction time sequence is considered, and the fraud detection accuracy and real-time performance are improved.

The application discloses a transaction timestamp injection data time sequence reconstruction method compatible with a cloud native architecture, a data production end acquires transaction data and uploads the transaction data to a cloud message queue, a data consumption end acquires the transaction data from the cloud message queue and injects transaction time acquired from a transaction house, the cloud acquires the transaction data injected with the transaction time, creates a partition according to the transaction time, and stores new transaction data in a hot data area and old transaction data in a cold data area. The application reconstructs the transaction data time sequence through authoritative time source injection, ensures transaction sequence authenticity, constructs a time sequence reconstruction scheme based on native database functions, designs a lightweight field injection mechanism, avoids invasive modification of cloud service APIs, establishes a lightweight data fault tolerance mechanism, improves data fault tolerance, and finally solves the fundamental contradiction between unordered storage of the cloud native architecture and financial time sequence requirements and the fault tolerance requirement.

According to one embodiment, there is presented herein a method of licensing, authenticating, and time stamping transactions associated with stored a digital media item. According to a first embodiment, there is provided a method of storing licensing terms in a blockchain token, which terms can be retrieved from the token and examined by someone interested in licensing the item. In still another variation there is provided a method of memorializing changes to a digital item as it undergoes reviews by creating a time stamp associated with each change and storing that in a blockchain token.

The invention relates to the technical field of big data, and provides a transaction data processing method and device based on idle time, equipment and a medium, which can start a business thread to scan a market queue and a return queue in real time in a current transaction period so as to respond in time. In the continuous scanning process of preset times, when no new market information slice is scanned in the market information queue and no new return information is scanned in the return queue, calculating the current idle time according to an idle time determination strategy after the market information and the return are ensured to be processed; the operator type with high real-time performance is divided into the pre-calculation operator and the decision operator, the pre-calculation operator is processed in the current idle time, the decision operator is processed in the current transaction time, the idle time can be fully utilized, glitch time delay in the transaction process is reduced, and the performance and time delay penetration stability of a transaction system are improved.

This invention relates to the field of AI-based risk control technology in financial payments, specifically to an AI-based real-time payment risk early warning method and system. The method includes: acquiring transaction behavior feature records containing standardized transaction amount ranges, transaction time slice distributions, and a relational graph of transaction participants; deconstructing the relational graph using a graph structure analyzer to extract potential indirect correlation paths between the transaction initiator and historical risk accounts, generating a risk correlation feature vector, and combining this with multi-dimensional behavioral analysis to obtain a behavioral deviation index; inputting the two types of features into a risk decision fusion model to obtain a comprehensive risk score; generating a dynamic risk threshold based on the risk level; triggering an early warning signal when the score exceeds the threshold, and generating an early warning instruction containing a risk cause code and interception suggestions. This method can uncover multi-level hidden risk correlations, dynamically adapt to the threshold settings for transaction risk levels, improve the completeness of risk feature extraction, and optimize the adaptation effect of risk early warning judgment.

The invention provides a block chain consensus optimization auditing method based on Beidou time service and a terminal. Comprising the following steps: providing unified time reference data for nodes in a block chain network based on a Beidou satellite time service system; when a transaction request is received, generating a transaction timestamp based on the unified time reference data, and generating a transaction global time sequence sorting result of all transaction requests according to the transaction timestamp; performing parallel verification and processing on all the transaction requests through a time window grouping technology by utilizing the transaction global time sequence sorting result to obtain a transaction parallel verification result; and based on the unified time reference data, the transaction global time sequence sorting result and the transaction parallel verification result, generating tamper-proof time audit log data, and storing the data in the block chain network. According to the method, the unified time reference of the block chain network is realized, the block chain consensus mechanism efficiency is optimized, and the performance, security and expandability of the system are improved.

The application relates to a kind of blockchain-based distributed energy transaction verification method and system, relate to the field of blockchain energy transaction, which includes the transaction parameters and identity parameters of the transaction collected;The collected transaction parameters and identity parameters are checked, and transaction code and identity code are determined;After verification, the matching hash value of the blockchain is determined based on the transaction code and the identity code;The matching hash value is converted into a paired string;When the paired string is added to 0, pairing is completed, transactions are carried out according to the transaction code, and data is uploaded to the blockchain platform, and the transaction is completed after the settlement is completed.The application has the effect of reducing transaction time and improving efficiency.

The application discloses an instant information publishing method, system and device supporting interactive transaction and a storage medium. According to the needs of actual power grid balanced operation in a control area or after the interactive transaction application of market subjects in the control area to a power transaction center is audited and passed, the power transaction center broadcasts interactive transaction information to all market subjects in the control area through a power transaction platform. In the transaction process, the market subjects can dynamically adjust the declared transaction information at any time. At this time, the power transaction center publishes transaction adjustment information to other market subjects in the whole range which have participated in the interactive transaction through the power transaction platform. After the transaction result is published or after the market subjects propose transaction termination application within the specified transaction time and obtain the approval of the power transaction center, the interactive transaction is ended. The application can realize instant publishing of interactive transaction information, meet the stability of transaction time and transaction cycle of the interactive transaction and promote the smooth development of the interactive transaction among the market subjects.

The application provides a transaction log collection method, device and system. The transaction log collection method comprises the following steps: putting log files of each application server into a cache queue; determining a time difference according to a tail transaction time and a head message transaction time; determining a log output time according to the time difference and the head message transaction time; sorting the log files in the cache queue according to transaction times in the log files, and putting the sorted log files into an output message queue according to the log output time. The application can effectively deal with a large number of logs generated in a short time, ensure that the collected logs are complete and orderly, avoid transaction failure, and further improve the playback efficiency and effect of a subsequent follow-up playback device.

An apparatus comprises at least one processing device configured to detect, utilizing a machine learning model, anomalous transactions in a database system comprising first and second databases, the second database having a configurable disaster recovery delay time period relative to the first database. The at least one processing device is also configured to determine a recovery time point for the database system based on a transaction time of a given anomalous transaction, and to replay, from the first database to the second database, a first set of transactions occurring during the configurable disaster recovery delay time period up to the determined recovery time point, to validate recovery of the first set of transactions, and to replay, from the first database to the second database, a second set of transactions of the database system occurring after the determined recovery time point responsive to validating recovery of the first set of transactions.

The invention discloses a business data processing method, device and equipment, a computer medium and a product, which are applied to the field of data processing, and the method comprises the following steps: obtaining transaction information of a transaction subject; constructing a first product detail table based on the transaction information of the transaction subject; the first product detail table comprises a transaction identifier, a transaction subject identifier, a product number, transaction data, transaction time and a transaction data source; receiving a business registration form input by the user, wherein the business registration form comprises a user identifier, an identifier of a transaction subject, registration time and a registration product; based on the transaction subject identifier, matching the business registration form with the first product detail table to obtain a second product detail table of the user; determining initial service data of the user based on the second product detail list and preset service data configuration parameters; summarizing the initial business data to obtain target business data of the user; and displaying the target business data. According to the method, the business data processing efficiency and accuracy can be improved.

The invention belongs to the technical field of settlement, and particularly relates to a peer-to-peer power transaction settlement method and system based on an alliance chain, and the method comprises the following steps: S1, obtaining to-be-settled power transaction data at least comprising two transaction parties, the key levels of the two transaction parties, the transaction electric quantity, the transaction price and the transaction time; s2, according to the historical transaction verification reliability and the power grid role identity of each consensus node, calculating to obtain a consensus weight of each consensus node; and calculating the whole-network consensus health degree according to the whole-network distribution of the consensus weight, and taking the whole-network consensus health degree as a regulatory factor. According to the method, false or wrong transactions which do not accord with rules can be filtered out before the data is linked, the authenticity and reliability of the on-chain power transaction data are guaranteed from the source, and the potential operation risk of a power grid is avoided.

The invention relates to an anti-money laundering suspicious transaction monitoring method and device, and relates to the field of data monitoring, and the method comprises the steps: monitoring transaction data of a target account, carrying out the extraction of a transaction amount sequence and a transaction timestamp sequence, and carrying out the calculation of a short-time transaction amount and a short-time transaction frequency; performing anomaly classification on the short-time transaction amount and the short-time transaction frequency to obtain a target amount anomaly coefficient and a target frequency anomaly coefficient; taking associated historical transaction monitoring data of a plurality of associated accounts in the associated account graph, carrying out abnormal classification on short-time transaction frequency, obtaining an associated frequency abnormal coefficient graph, carrying out fitting to obtain an associated frequency abnormal coefficient, combining a target amount abnormal coefficient with a target frequency abnormal coefficient, calculating to obtain a transaction abnormal coefficient, and judging to obtain a monitoring result. The technical problems that in the prior art, money laundering suspicious transaction monitoring is mostly carried out through simple judgment rules, accurate monitoring and recognition are difficult to carry out on multi-level transactions, and the monitoring accuracy is low are solved.

The application relates to a user type determination method and device, computer equipment and a storage medium, and relates to the field of artificial intelligence. The method comprises the following steps: obtaining target transaction data of a to-be-detected user; determining transaction time sequence features corresponding to the target transaction data based on a preset feature extraction algorithm and a data standard format, wherein the transaction time sequence features comprise fixed-length feature data of the to-be-detected user; inputting the transaction time sequence features of the to-be-detected user into a trained user type prediction model to obtain a type prediction result of the user type prediction model, and determining a user type of the to-be-detected user based on the type prediction result. The method can improve the prediction accuracy of a prediction model for predicting abnormal users with abnormal transaction behaviors.

The application provides a transaction execution method and device of a blockchain, electronic equipment and a storage medium, and relates to the technical field of blockchains. The method increases the attack cost of an attacker, designs contract content of a smart contract from multiple dimensions such as transaction time and transaction fee and transaction frequency, to alleviate the influence of the attacker on the contract execution result by increasing the transaction fee to make his own transaction preferentially executed; by combining historical transaction information, the transaction request is successfully executed only when the cumulative execution information of the transaction request of the same transaction content meets the set condition of the smart contract, which can avoid the unfair phenomenon of transaction execution caused by the fact that the transaction execution order depends on the transaction fee and the transaction is successfully executed only by one execution, thereby effectively avoiding the influence of the attacker on the transaction execution result caused by maliciously increasing the transaction fee, and improving the transaction experience of the transaction request party.

The invention provides an index aperture conflict identification method and system based on AI training and reasoning cooperative scheduling, and the method comprises the steps: obtaining a transaction initiation timestamp of a multi-warehouse allocation record from a database of an inventory management system, and recognizing in-transit commodities, and a warehouse-out confirmation moment and a target warehouse-in registration moment corresponding to the in-transit commodities, sorting the warehouse-out confirmation time and the target warehouse-in registration time to obtain an ordered transaction time list; according to the caliber conflict type, identifying an in-transit commodity attribution state in each warehouse allocation link, the in-transit commodity attribution state including a warehouse-out and non-warehouse-in state and a state that downstream warehouse allocation depends on upstream warehouse inventory; and performing real-time comparison according to a real stock time sequence and a time sequence accumulated stock value, evaluating whether the deviation exceeds a preset aperture conflict identification range, triggering an aperture conflict identification alarm, and recording a conflict type, a distribution range of potential aperture conflicts and a related transaction initiation timestamp into a management system log.

A device, system and method for accelerated compliance testing for real-time detection of suspicious transactions in a transaction stream. A machine learning model may determine a global trend of cumulative transaction behavior based on all, a majority or a representative subset, of the stream of transactions. For each transaction in the stream, a skip rule engine may sort each security compliance test to be skipped or not skipped based on the test's relevance to the global trend of the cumulative transaction behavior. The not skipped security compliance tests may be executed in real-time for each transaction in the stream to generate real-time partial security assessments therefore comprising real-time suspicious transaction alerts. The remaining tests may be skipped in real-time and executed, at a time delay after transaction times, to generate time delayed supplemental security assessments therefore comprising time delayed suspicious transaction alerts to complete all compliance testing.

The invention discloses an asset transaction risk monitoring system and method, and relates to the field of asset transaction security. The method comprises the following steps: acquiring transaction object types, transaction time, transaction amount and flow funds through a plurality of transaction objects of a user; calculating a transaction frequency index according to the transaction time of different transaction objects; collecting multiple groups of asset risk training data through historical transaction data of multiple users; each group of asset risk training data comprises the transaction object type, the transaction frequency index and the transaction total amount ratio of a plurality of historical transaction objects of each user, and a risk mark indicating whether each transaction object has a flow fund risk, and training to obtain an asset risk prediction model.

This invention discloses a method and system for intelligent matching of preferred products based on user profiles, specifically relating to the field of e-commerce data processing technology. The method includes obtaining user account rights transaction records, filtering transaction lines based on payment completion markers, using the receiving field as the object primary key, forming an occupancy interval based on the start and end times of rights, and attaching the redemption time and purchase price to output a successful purchase table; merging the successful purchase tables by object primary key and forming an observation sequence based on transaction time, forming a preference continuation factor based on the primary key, a demand occupancy factor based on the intersection of intervals, and a price response factor based on the price difference following the purchase result, outputting a factor graph; extracting the object primary key, occupancy interval, purchase price, and redemption feedback from successful transaction records, constructing a factor graph, and separating the preference retention state and demand extinction state using a factor hidden Markov model algorithm, and then generating a purchase suppression set and a purchase strategy sequence using a particle learning algorithm and a strategy price determination process.

The application provides a blockchain offline data updating method and device, electronic equipment and readable medium. The method can acquire at least two to-be-processed blocks in a blockchain, wherein each to-be-processed block contains a to-be-processed transaction for a virtual resource transaction; for each to-be-processed block, the to-be-processed block is parsed by a corresponding parsing container to obtain the to-be-processed transaction, wherein each to-be-processed block is processed by one parsing container; for each to-be-processed transaction, other transactions of the virtual resource are acquired from the blockchain offline data by the parsing container; and according to the latest transaction in the to-be-processed transaction and the other transactions, a transaction record of the virtual resource in the blockchain offline data is updated. The method can ensure that the transaction record with the latest transaction time is saved in the blockchain offline data, and the accuracy of the blockchain offline data is improved.

Embodiments of the present application provide a kind of based on atlas's association relationship screening method and device, applied in artificial intelligence technical field, comprising: obtaining historical transaction data, and based on historical transaction data, constructs transaction association graph;Based on the transaction time of each transaction in historical transaction data, transaction association graph is split into multiple association subgraphs, each association subgraph includes a time period node and associated user node and transaction object node;Multiple association subgraphs are clustered, and multiple clustering sets are obtained;For each clustering set, multiple association subgraphs in clustering set are atlas fusion, obtain sequence fusion subgraph, and determine overlapping target association subgraph from sequence fusion subgraph.The behavior sequence of user and the association relationship of atlas are fused in the present application, the common behavior data is clustered by the method of clustering, can excavate strong centricity user transaction behavior, improve the analysis efficiency and accuracy to point arbitrage behavior.

This application relates to a transaction reconciliation method, apparatus, device, and storage medium, applied to a reconciliation system. The reconciliation system is communicatively connected to a business system. The method includes: after listening to business event information sent by the business system, obtaining the current transaction data, current transaction fee, and current transaction time corresponding to the business event information; determining whether the current transaction time is less than the transaction time of a target business event in a preset transaction record table; if less, sorting the business events in ascending order according to the transaction time in the preset transaction record table, and calculating the transaction data corresponding to the business events according to the sequence until the target transaction fee corresponding to the business event information is obtained; and reconciling the target transaction fee with the current transaction fee to obtain the first reconciliation result data. The solution provided by this application solves the problem of cumulative calculation deviation caused by time sequence disorder in high-concurrency transactions, and can improve the accuracy and reliability of transaction reconciliation.

The embodiment of the application provides a bill record method, which is used for realizing quick recording of multiple accounts and multiple platform accounts, thereby improving the recording accuracy and recording efficiency. It can be applied to the fields of computers, bill recording, etc. It comprises the following steps: a first interface is displayed, the first interface is used for displaying a transaction data set and a bill creation control, the transaction data set comprises N pieces of transaction data, N is a positive integer greater than 1, and the N pieces of transaction data are derived from at least one transaction channel; in response to an operation on the bill creation control, bill information is generated based on the transaction data set and the bill information is displayed, the bill information comprises a bill record and a bill type, the bill record is used for recording transaction amounts, transaction times and transaction objects of the transaction data in the transaction data set, the bill type is used for describing transaction types of the transaction data in the transaction data set, and the bill information is generated based on image recognition or voice recognition on the transaction data set.

The embodiment of the invention relates to the technical field of databases, and discloses a financial product screening method, device and equipment and a storage medium, and the method comprises the steps: determining screening indexes, and dividing the screening indexes into real-time indexes and non-real-time indexes; non-real-time data is synchronized from a non-real-time index data system before opening the market, and is stored in a local database; in the transaction time period, synchronizing real-time data from a real-time system of the real-time index every preset time, and reading non-real-time data from a local database; after the real-time data is acquired each time, combining the non-real-time data and the latest real-time data, and storing the combined data into a memory database; and receiving a screening condition of the client, reading the total data from the memory database, and screening according to the total data and the screening condition to obtain a target financial product set. By means of the mode, quick extraction of cross-system and multi-timeliness data is achieved, data extraction and screening logic execution operation are efficient, and performance is better.

A method for authenticating a transaction includes identifying a first transaction made at a first physical location that includes a first transaction time; receiving a request for a second transaction; and identifying the requested second transaction is made at a second physical location that includes a second transaction time. The method further includes computing, using encryption, a distance between the first and second physical location; computing a minimum speed to transition between the first and second location in a delta time between the first transaction time and the second transaction time; comparing the computed minimum speed to a threshold; and determining whether the requested second transaction is authentic in response to comparing the computed minimum speed to the threshold. In this manner, determining a distance, time delay and therefore minimum speed between two consecutive transactions provides an additional authentication using encryption.

The invention discloses a transaction-level SLA fracture positioning method and system, and belongs to the field of network application performance monitoring and service quality assurance. The method comprises the steps of firstly collecting network flow data and constructing a transaction unique identifier ID, generating a structured account book data object according to transaction information, calculating baseline drift and an attribution function of a transaction path segment, calculating the attribution function of each segment to identify a responsibility segment causing SLA fracture when a transaction total time delay is greater than a fixed threshold value, and obtaining a structured account book data object; and finally, calculating a path health index based on the stability index of each segment of the transaction to evaluate the transaction path. According to the method, the transaction path is subjected to segmented modeling, the attribution contribution value of each segment is calculated, so that the SLA anomaly can be accurately positioned to a specific path segment, the anomaly positioning precision is improved, the method can quickly identify a related responsibility segment, the troubleshooting time is shortened, a long-term hotspot segment is identified through cross-transaction statistical analysis, and the service life of the SLA is prolonged. And a basis is provided for system performance optimization and resource configuration.

The invention relates to the technical field of computers, and provides a data display method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring transaction time sequence data of a to-be-displayed object; the transaction time sequence data comprises prices of the to-be-displayed object at different time-sharing points of each transaction day; displaying the transaction time sequence data in a three-dimensional space of the data display interface; the three-dimensional space comprises a three-dimensional main coordinate system, and three coordinate axes of the main coordinate system respectively bear trading days, time-sharing points and prices in the trading time sequence data. According to the data display method and device, the electronic equipment, the storage medium and the program product provided by the invention, a user can be supported to intuitively observe the occurrence time and the distribution rule of different prices in the time sequence.

The invention discloses a power grid resource trusted transaction management method based on a block chain, terminal equipment and a storage medium, and belongs to the field of power systems, the method comprises the following steps: screening matched candidate resources according to the resource type, reputation score, resource state and transaction quotation information of to-be-transacted resources; for each candidate resource, calculating a matching score of the candidate resource according to the reputation score, the resource state and the transaction quotation information; taking the candidate resource with the highest matching score as another resource to be transacted, and generating a corresponding transaction ID and a transaction timestamp; according to the transaction ID, the transaction timestamp, the transaction volume, the resource ID and the signature of the to-be-transacted resource, and the resource ID and the signature of the other to-be-transacted resource, generating a transaction credible certificate, and writing the transaction credible certificate into the block chain; and the two transaction parties perform transaction. By implementing the method and the device, the problems that a traditional centralized management mode cannot effectively guarantee the credibility of transactions and cannot realize rapid and accurate resource matching can be solved.

The invention provides a self-adaptive association interaction synchronization method and system for overdue value keeping service data, and relates to the technical field of data synchronization, and the method comprises the following steps: a parallel API interface captures a parallel original service data flow of a parallel overdue protection core data system; parallel time sequence material coding features and parallel time sequence transaction timestamps are extracted, cross-system transaction service association matching is carried out, and P service process states of P associated service chains are obtained; performing dynamic closed-loop updating on the financial data; acquiring multi-source increment change captured by the CDC by monitoring an asynchronous message queue, performing business process exception identification, and outputting business process update information; and performing financial data exception rollback, and performing sleeve insurance service state synchronization. According to the method and the device, the technical problems of low data integration efficiency and high error rate caused by the fact that most of data synchronization modes in the prior art depend on a static data mapping rule, are lack of flexibility and are difficult to adapt to the dynamic change of the set value keeping service are solved.

The application provides an abnormal transaction monitoring method, device, equipment, medium and program product, which can be applied to the field of artificial intelligence technology. The method comprises the following steps: acquiring transaction data, and generating a transaction time sequence by using a preset sliding time window according to the transaction data; inputting the transaction time sequence into a pre-trained multi-task deep learning model to obtain a transaction success rate and a transaction failure reason, wherein the multi-task deep learning model is integrated with a regression task prediction layer and a classification task identification layer, the regression task prediction layer is used for regression calculation according to the transaction time sequence, and outputs a transaction success rate prediction value in a next time window, and the classification task identification layer is used for classification calculation according to the transaction time sequence, and outputs a probability distribution of the transaction failure reason; determining a dynamic alarm threshold according to the transaction success rate prediction value in the next time window; and monitoring an actual transaction success rate according to the dynamic alarm threshold.