Secure transaction pairing method and system under delivery service platform

Abstract

The invention discloses a secure transaction pairing method and system under a delivery service platform, relates to the technical field of financial science and technology, and ensures the legality and integrity of a transaction request through multiple cross verification steps of identity consistency verification, transaction application time verification, fund verification and the like; particularly, malicious control behaviors such as frequent automatic transaction requests can be recognized in time by analyzing the operation frequency of the user, so that interference of malicious users or program scripts on the market is effectively prevented, and the safety of the platform is improved; according to the invention, the transaction request of the user and other transaction requests on the platform are combined to carry out intelligent transaction matching and recommendation; by calculating the matching degree and the comprehensive score of the transaction, the platform can provide personalized transaction recommendation for the user, identify potential high-risk transactions according to the risk score, trigger additional identity verification in time, and ensure the stability and the security of platform transactions.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to a secure transaction matching method and system under a delivery service platform. Background Art

[0002] With the rapid development of modern financial markets, various trading services provided by exchanges and financial platforms have gradually become electronic, automated and intelligent. Financial platforms involve a large number of transaction requests and fund operations, and the processing of these transactions must ensure their legality, security and efficiency. Especially in the fields of financial derivatives trading, stock trading and cryptocurrency trading, the high frequency and complexity of transactions pose more severe challenges to the security of the platform.

[0003] Currently, many trading platforms have not fully adopted effective encryption technology to protect transaction data. Unencrypted transaction data may be attacked by hackers, resulting in user privacy leakage or transaction data tampering, and in serious cases may even lead to transaction fraud and damage user interests.

[0004] In addition, current trading platforms rely on simple identity authentication to verify trading requests, lacking in-depth multi-verification and abnormal behavior detection mechanisms. For example, malicious users or automated scripts may manipulate the market by submitting a large number of frequent trading requests, and existing systems often cannot detect these abnormal behaviors in a timely manner.

[0005] In view of the above problems, it is necessary to propose a secure transaction matching method and system under the delivery service platform. Summary of the invention

[0006] The purpose of the present invention is to solve the problems existing in the background technology and to propose a secure transaction matching method and system under a delivery service platform.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A secure transaction matching method and system under a delivery service platform.

[0009] In a first aspect, the present invention provides a secure transaction matching method under a delivery service platform, comprising the following steps:

[0010] Step 1: Receive and encrypt transaction request;

[0011] The transaction request data submitted by the user in each transaction application is obtained on the delivery service platform, including the user name Name, transaction type symbol Type, transaction quantity Quantity, price Price, underlying asset number symbol Asset, margin amount Margin, transaction application time Time and transaction account Account.

[0012] Among them, the specific value of the transaction type symbol corresponds to a preset transaction type, including buy, sell, close, take profit and stop loss.

[0013] Collect all transaction request data submitted by the user in each transaction application, and generate a transaction identifier UID(i)={Name(i), Type(i), Quantity(i), Price(i), Asset(i), Margin(i), Time(i), Account(i)} for each transaction application. i is the sequential number of each transaction identifier, i=1, 2, ..., n; n is the total number of transaction identifiers.

[0014] All transaction identifiers are encrypted and stored, encrypted using the AES symmetric encryption algorithm, and the encrypted results are stored in the database to ensure the confidentiality and non-tamperability of the data.

[0015] Step 2: Transaction security cross-verification;

[0016] In subsequent transaction processing, the transaction request data in all transaction identifiers are cross-verified to ensure the legitimacy and integrity of the transaction request.

[0017] Among them, cross-verification includes identity consistency verification, transaction application time verification and funds verification.

[0018] The specific process of identity consistency verification is: obtain the user name and trading account in the transaction identifier, obtain the historical identity verification record of the user name from the database, and check whether the trading account currently submitting the request is consistent with the historical record. If the user has not performed identity verification in the platform or there is an abnormality in the account information, the identity verification alarm will be triggered and the transaction request will be terminated. If the trading account corresponding to the user name has multiple login failures, the user will be required to re-authenticate.

[0019] The specific process of transaction application time verification is as follows: extract the transaction application time from the transaction identifier, count the number of transaction requests initiated by the same user name in each preset time interval, and record it as the user's operation frequency in each preset time interval. If the user's operation frequency in the previous preset time interval exceeds the preset threshold, the time verification alarm is triggered and the transaction request is terminated.

[0020] The specific process of fund verification is: extract the trading account from the transaction identifier, query the balance in the account, and ensure that the account balance in the user's trading account is greater than the preset minimum margin amount, otherwise the fund verification alarm is triggered and the transaction request is terminated.

[0021] If the transaction request data in the transaction identifier passes the identity consistency verification, transaction application time verification and fund verification, the corresponding transaction application is allowed to enter the transaction sorting and transaction recommendation procedure.

[0022] Step 3: Transaction sorting and recommendation;

[0023] After the transaction identifier data passes identity consistency verification, transaction application time verification and fund verification, it enters the recommendation and transaction sorting program to provide browsing references and recommendations for both parties to the transaction.

[0024] The specific process of transaction recommendation is as follows:

[0025] Obtain the transaction type symbol, underlying asset number symbol, transaction quantity, price, and transaction application time corresponding to the transaction request data in each transaction application, and record them as Type (0), Asset (0), Quantity (0), Price (0), and Time (0), respectively.

[0026] For the transaction type identifier, obtain the specific value of Type (0) in the transaction application. Obtain the transaction identifiers corresponding to all other transaction applications on all delivery service platforms except this transaction application, and extract Type (i), i = 1, 2, 3, ..., n; traverse all Type (i), calculate the result Strategy (i) of Type (0) + Type (i); the specific value of Strategy (i) represents the matching rule between the transaction identifier of this transaction application and the transaction identifier i.

[0027] As a preferred embodiment of the present invention, a browsing and searching window is provided to each user through a UI interface, allowing the user to choose to view other transaction types matching his / her current transaction application according to his / her own will.

[0028] For the asset identifier, transaction quantity, price and transaction application time, obtain the transaction identifiers corresponding to all transaction applications on all delivery service platforms except this transaction application, and extract the transaction quantity Quantity (i), the asset identifier Asset (i), the price Price (i) and the transaction application time Time (i).

[0029] By preset formula Calculate the object matching score P0(i).

[0030] By preset formula Calculate the quantity matching score P1(i), price matching score P2(i) and transaction application time matching score P3(i). The matching degree Match(i) between this transaction application and transaction identifier i is calculated using the preset formula Match(i)=P0(i)×{K1×P1(i)+K2×P2(i)+K3×P3(i)}.

[0031] As a preferred mode of the present invention, a browsing and searching window is provided for each user through the UI interface, allowing the user to select and view other transaction identifiers that meet the matching degree, transaction quantity, price and transaction application time range according to his / her own will, and providing a window to sort these search results in ascending or descending order. The UI interface provides the setting of the numerical range of each search parameter, and the selection of whether to sort in ascending or descending order, so as to perform personalized transaction screening and recommendation.

[0032] Step 4: Transaction scoring and anomaly detection;

[0033] After the user selects the transaction object and completes a transaction match, further information about both parties is obtained, including the number of all transaction matches c1 and c2 completed by both parties within the set time window T, and the final price of the transaction match. and the final transaction quantity ;

[0034] Get the average transaction price of the asset ID matched in this transaction on the delivery service platform, and record it as the market price ; Get the average transaction quantity of the asset ID symbol Asset matched in this transaction on the delivery service platform in each transaction match, and record it as the market average transaction quantity ; Through the preset formula Calculating transaction frequency score , Transaction Price Rating and transaction quantity score .in This is the matching frequency characteristic value of the two parties in this transaction matching; is the standard reference value for matching frequency characteristic value; where α is the preset adjustment factor.

[0035] By preset formula Calculate the risk characteristic value Risk of this transaction match; w1, w2 and w3 are preset scoring weights, and the specific numerical values ​​of the scoring weights are set according to the platform's risk tolerance and risk prevention strategy.

[0036] If the risk feature value Risk is greater than the preset threshold, the transaction match is judged to have a high risk, and additional identity verification is required from both parties to the transaction, including one or more combinations of SMS verification code of the bound number, facial recognition, and fingerprint recognition.

[0037] In a second aspect, the present invention provides a secure transaction matching system under a delivery service platform, including a transaction request receiving and encryption module, a database, a transaction security cross-verification module, a sorting and recommendation module, a transaction scoring and anomaly detection module, and an identity authentication and security module.

[0038] The transaction request receiving and encryption module obtains basic information from the transaction application submitted by the user, including user name, transaction type, quantity, price, underlying asset number, margin amount, time and trading account. A unique transaction identifier is generated for each transaction application, which contains all transaction request information. The transaction request data is encrypted using the AES symmetric encryption algorithm to ensure the confidentiality and non-tamperability of the data during storage and transmission. The encrypted transaction identifier is stored in the database to ensure the security of the transaction data.

[0039] The database saves all transaction identifiers and identity information of all users and stores them in encrypted form.

[0040] The transaction security cross-verification module ensures the legitimacy of the account submitting the request by comparing the account in the transaction request with the historical identity authentication records stored in the database.

[0041] As a preferred method of the present invention, the transaction frequency of users in different time intervals is analyzed to identify abnormal behaviors of frequently submitting transaction requests and prevent malicious manipulation.

[0042] As a preferred embodiment of the present invention, the balance in the user's trading account is checked to ensure that the account balance is greater than or equal to the minimum margin required for the transaction.

[0043] The sorting and recommendation module calculates transaction matching rules based on transaction type identifiers, subject matter number identifiers and other parameters, matches transaction applications with other transaction identifiers according to the rules, and calculates the matching degree between transaction applications and other transactions through a preset matching formula.

[0044] As a preferred embodiment of the present invention, a visual interactive interface is provided to the user, allowing the user to filter transaction objects according to transaction matching degree, price, quantity, etc., and select matching rules according to personal needs.

[0045] The transaction scoring and anomaly detection module calculates transaction frequency, price, quantity and other indicators through a preset scoring formula, and gives a comprehensive score for both parties to the transaction.

[0046] As a preferred method of the present invention, the risk characteristic value of the transaction is obtained by weighted calculation based on data such as transaction frequency score, price score, quantity score, etc. If the risk score exceeds the preset threshold, it is determined to be a high-risk transaction.

[0047] The authentication and security module is equipped with a facial recognition camera, fingerprint recognition unit and SMS verification unit for multi-factor authentication. When a transaction is judged to be high risk, the user is required to verify through multiple authentication methods such as SMS verification code, facial recognition or fingerprint recognition.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1. The present invention ensures the legitimacy and integrity of transaction requests through multiple cross-verification steps such as identity consistency verification, transaction application time verification and fund verification. In particular, by analyzing the user's operation frequency, malicious manipulation behaviors such as frequent automatic transaction requests can be identified in a timely manner, thereby effectively preventing malicious users or program scripts from interfering with the market and improving the security of the platform;

[0050] 2. The present invention combines the user's transaction request with other transaction requests on the platform to perform intelligent transaction matching and recommendation. By calculating the matching degree and comprehensive score of the transaction, the platform can provide personalized transaction recommendations to users, identify potential high-risk transactions based on risk scores, and trigger additional identity verification in a timely manner to ensure the stability and security of platform transactions;

[0051] 3. The present invention uses the AES symmetric encryption algorithm to encrypt transaction request data, ensuring the confidentiality and non-tamperability of transaction data. During data storage and transmission, it effectively prevents data leakage and tampering risks, providing users with a safe and reliable transaction environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings:

[0053] Figure 1 is a flow chart of the method of the present invention;

[0054] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0055] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] See also Figure 1 As shown, a secure transaction matching method under a delivery service platform includes the following steps:

[0057] Step 1: Receive and encrypt transaction request;

[0058] The transaction request data submitted by the user in each transaction application is obtained on the delivery service platform, including the user name Name, transaction type symbol Type, transaction quantity Quantity, price Price, underlying asset number symbol Asset, margin amount Margin, transaction application time Time and transaction account Account.

[0059] Among them, the specific value of the transaction type symbol corresponds to a preset transaction type, including buy, sell, close, take profit and stop loss.

[0060] Specifically, the buy transaction type symbol Type=1;

[0061] The transaction type of the sell transaction is Type=2;

[0062] The transaction type of the closed transaction is Type=3;

[0063] The transaction type symbol of the take-profit transaction is Type=4;

[0064] The transaction type symbol of stop loss transaction is Type=5;

[0065] Collect all transaction request data submitted by the user in each transaction application, and generate a transaction identifier UID(i)={Name(i), Type(i), Quantity(i), Price(i), Asset(i), Margin(i), Time(i), Account(i)} for each transaction application. i is the sequential number of each transaction identifier, i=1, 2, ..., n; n is the total number of transaction identifiers.

[0066] All transaction identifiers are encrypted and stored, encrypted using the AES symmetric encryption algorithm, and the encrypted results are stored in the database to ensure the confidentiality and non-tamperability of the data.

[0067] Step 2: Transaction security cross-verification;

[0068] In subsequent transaction processing, the transaction request data in all transaction identifiers are cross-verified to ensure the legitimacy and integrity of the transaction request.

[0069] Among them, cross-verification includes identity consistency verification, transaction application time verification and funds verification.

[0070] The specific process of identity consistency verification is: obtain the user name and trading account in the transaction identifier, obtain the historical identity verification record of the user name from the database, and check whether the trading account currently submitting the request is consistent with the historical record. If the user has not performed identity verification in the platform or there is an abnormality in the account information, the identity verification alarm will be triggered and the transaction request will be terminated. If the trading account corresponding to the user name has multiple login failures, the user will be required to re-authenticate.

[0071] The specific process of transaction application time verification is as follows: extract the transaction application time from the transaction identifier, count the number of transaction requests initiated by the same user name in each preset time interval, and record it as the user's operation frequency in each preset time interval. If the user's operation frequency in the previous preset time interval exceeds the preset threshold, the time verification alarm is triggered and the transaction request is terminated.

[0072] It should be noted that malicious users or program scripts may submit a large number of transaction requests in a short period of time in an attempt to maliciously manipulate market prices or conduct transaction fraud. Transaction application time verification analyzes the frequency of transaction requests to detect whether there are abnormal frequent transaction application behaviors in the transaction, and prevent malicious transactions automatically performed by robots and scripts.

[0073] The specific process of fund verification is: extract the trading account from the transaction identifier, query the balance in the account, and ensure that the account balance in the user's trading account is greater than the preset minimum margin amount, otherwise the fund verification alarm is triggered and the transaction request is terminated.

[0074] If the transaction request data in the transaction identifier passes the identity consistency verification, transaction application time verification and fund verification, the corresponding transaction application is allowed to enter the transaction sorting and transaction recommendation procedure.

[0075] Step 3: Transaction sorting and recommendation;

[0076] After the transaction identifier data passes identity consistency verification, transaction application time verification and fund verification, it enters the recommendation and transaction sorting program to provide browsing references and recommendations for both parties to the transaction.

[0077] The specific process of transaction recommendation is as follows:

[0078] Obtain the transaction type symbol, underlying asset number symbol, transaction quantity, price, and transaction application time corresponding to the transaction request data in each transaction application, and record them as Type (0), Asset (0), Quantity (0), Price (0), and Time (0), respectively.

[0079] For the transaction type identifier, obtain the specific value of Type (0) in the transaction application. Obtain the transaction identifiers corresponding to all other transaction applications on all delivery service platforms except this transaction application, and extract Type (i), i = 1, 2, 3, ..., n; traverse all Type (i), calculate the result Strategy (i) of Type (0) + Type (i); the specific value of Strategy (i) represents the matching rule between the transaction identifier of this transaction application and the transaction identifier i.

[0080] Specifically, a Strategy (i) value of 3 represents a buy-sell match;

[0081] Strategy (i) value 4 represents buy-close matching;

[0082] Strategy (i) value 5 represents buy-take profit matching;

[0083] Strategy(i)=3 means buy-sell matching;

[0084] Strategy(i)=4 means buy-close matching;

[0085] Strategy(i)=5 means buy-take-profit matching;

[0086] Strategy(i)=6 means buy-stop matching;

[0087] Strategy(i)=3 means sell-buy matching;

[0088] Strategy(i)=5 means sell-close matching;

[0089] Strategy(i)=6 means sell-take-profit matching;

[0090] Strategy(i)=7 means sell-stop loss matching;

[0091] Strategy(i)=4 means close-buy match;

[0092] Strategy(i)=5 means close position - sell match;

[0093] Strategy(i)=7 means close position - take profit matching;

[0094] Strategy(i)=8 means closing position - stop loss matching;

[0095] Strategy(i)=5 means take profit-buy match;

[0096] Strategy(i)=6 means take profit-sell matching;

[0097] Strategy(i)=7 means take profit-close position matching;

[0098] Strategy(i)=9 means take profit-stop loss matching;

[0099] Strategy(i)=6 means stop loss-buy matching;

[0100] Strategy(i)=7 means stop loss-sell matching;

[0101] Strategy(i)=8 means stop loss-close position matching;

[0102] Strategy(i)=9 means stop loss-take profit matching;

[0103] Furthermore, a browsing and retrieval window is provided for each user through the UI interface, allowing the user to choose to view other transaction types that match his or her current transaction application according to his or her own wishes.

[0104] For example, if the transaction type symbol Type(0) of a transaction application is 1, and the matching rule selected by the user in the UI interface is Buy-Sell, then all transaction identifiers with Strategy(i)=3 are retrieved for output and display.

[0105] For the asset identifier, transaction quantity, price and transaction application time, obtain the transaction identifiers corresponding to all transaction applications on all delivery service platforms except this transaction application, and extract the transaction quantity Quantity (i), the asset identifier Asset (i), the price Price (i) and the transaction application time Time (i).

[0106] By preset formula Calculate the object matching score P0(i).

[0107] By preset formula Calculate the quantity matching score P1(i), price matching score P2(i) and transaction application time matching score P3(i). The matching degree Match(i) between this transaction application and transaction identifier i is calculated using the preset formula Match(i)=P0(i)×{K1×P1(i)+K2×P2(i)+K3×P3(i)}.

[0108] Furthermore, a browsing and search window is provided for each user through the UI interface, allowing the user to select and view other transaction identifiers that meet the matching degree, transaction quantity, price and transaction application time range according to his / her own will, and a window is provided to sort these search results in ascending or descending order. The UI interface provides the setting of the value range of each search parameter, and the selection of whether to sort in ascending or descending order, so as to personalize the transaction screening and recommendation.

[0109] For example, if the user selects that the transaction quantity is between 100 and 500, the price is between 20 and 50, and sorts in descending order of matching degree, then the transactions that meet the requirements will be filtered out based on these conditions and displayed in the search window in descending order of matching degree.

[0110] Step 4: Transaction scoring and anomaly detection;

[0111] After the user selects the transaction object and completes a transaction match, further information about both parties is obtained, including the number of all transaction matches c1 and c2 completed by both parties within the set time window T, and the final price of the transaction match. and the final transaction quantity ;

[0112] Get the average transaction price of the asset ID matched in this transaction on the delivery service platform, and record it as the market price ; Get the average transaction quantity of the asset ID symbol Asset matched in this transaction on the delivery service platform in each transaction match, and record it as the market average transaction quantity ; Through the preset formula Calculating transaction frequency score , Transaction Price Rating and transaction quantity score .in This is the matching frequency characteristic value of the two parties in this transaction matching; is the standard reference value for matching frequency characteristic value; where α is the preset adjustment factor.

[0113] By preset formula Calculate the risk characteristic value Risk of this transaction match; w1, w2 and w3 are preset scoring weights, and the specific numerical values ​​of the scoring weights are set according to the platform's risk tolerance and risk prevention strategy.

[0114] If the risk feature value Risk is greater than the preset threshold, the transaction match is judged to have a high risk, and additional identity verification is required from both parties to the transaction, including one or more combinations of SMS verification code of the bound number, facial recognition, and fingerprint recognition.

[0115] See also Figure 2As shown, a secure transaction matching system under a delivery service platform includes a transaction request receiving and encryption module, a database, a transaction security cross-verification module, a sorting and recommendation module, a transaction scoring and anomaly detection module, and an identity authentication and security module.

[0116] The transaction request receiving and encryption module obtains basic information from the transaction application submitted by the user, including user name, transaction type, quantity, price, underlying asset number, margin amount, time and trading account. A unique transaction identifier is generated for each transaction application, which contains all transaction request information. The transaction request data is encrypted using the AES symmetric encryption algorithm to ensure the confidentiality and non-tamperability of the data during storage and transmission. The encrypted transaction identifier is stored in the database to ensure the security of the transaction data.

[0117] The database saves all transaction identifiers and identity information of all users and stores them in encrypted form.

[0118] The transaction security cross-verification module ensures the legitimacy of the account submitting the request by comparing the account in the transaction request with the historical identity authentication records stored in the database.

[0119] Furthermore, the transaction frequency of users in different time intervals is analyzed to identify abnormal behaviors such as frequent submission of transaction requests and prevent malicious manipulation.

[0120] Furthermore, the balance in the user's trading account is checked to ensure that the account balance is greater than or equal to the minimum margin required for the transaction.

[0121] The sorting and recommendation module calculates transaction matching rules based on parameters such as transaction type identifier and underlying asset number identifier, such as buy-sell, sell-stop loss, etc., and matches transaction applications with other transaction identifiers according to the rules, and calculates the matching degree between transaction applications and other transactions through a preset matching formula.

[0122] Furthermore, a visual interactive interface is provided to users, allowing them to filter transaction objects based on transaction matching degree, price, quantity, etc., and select matching rules according to personal needs.

[0123] The transaction scoring and anomaly detection module calculates transaction frequency, price, quantity and other indicators through a preset scoring formula, and gives a comprehensive score for both parties to the transaction.

[0124] Furthermore, based on the transaction frequency score, price score, quantity score and other data, the risk characteristic value of the transaction is obtained through weighted calculation. If the risk score exceeds the preset threshold, it is determined to be a high-risk transaction.

[0125] The authentication and security module is equipped with a facial recognition camera, fingerprint recognition unit and SMS verification unit for multi-factor authentication. When a transaction is judged to be high risk, the user is required to verify through multiple authentication methods such as SMS verification code, facial recognition or fingerprint recognition.

[0126] It should be understood that the terms “include” and “comprising” used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0127] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and the claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and the claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations;

[0128] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A secure transaction matching method under a delivery service platform, characterized in that: The following steps are involved: Step 1: Receive and encrypt transaction request; Receive transaction request data submitted by users, including user information, transaction type, quantity, price, underlying asset number and margin amount, generate a unique transaction identifier for each transaction request, and encrypt and store it using the AES symmetric encryption algorithm; Step 2: Transaction security cross-verification; During the transaction request processing, the data in the transaction identifier is cross-verified multiple times; identity consistency verification is used to ensure that the user and account information match, and transaction application time verification is used to detect abnormal operation frequency; funds verification is used to ensure that the account balance meets the margin required for the transaction; only transaction requests that pass all verifications can enter subsequent processing; Step 3: Transaction sorting and recommendation; Calculate the matching degree between the transaction request and other transaction identifiers based on parameters including transaction type, underlying asset number, transaction quantity, price and time, and make transaction recommendations; support users to browse and filter transactions that meet their needs through the UI interface; Step 4: Transaction scoring and anomaly detection; After the user completes the transaction matching, the historical behavior, transaction frequency, transaction price and transaction volume of the two parties are further evaluated, and the risk characteristics contained in the transaction risk characteristic value is calculated through a preset formula; If the risk feature value exceeds the threshold, both parties to the transaction are required to perform additional identity authentication, including one or a combination of SMS verification code of the bound number, facial recognition, and fingerprint recognition.

2. A secure transaction matching method under a delivery service platform according to claim 1, characterized in that: The specific process of receiving transaction request data submitted by the user is as follows: Obtain the transaction request data submitted by the user in each transaction application on the delivery service platform, including the user name Name, transaction type symbol Type, transaction quantity Quantity, price Price, underlying asset number symbol Asset, margin amount Margin, transaction application time Time and transaction account Account; The specific value of the transaction type symbol corresponds to a preset transaction type, including buy, sell, close, take profit and stop loss; Collect all transaction request data submitted by the user in each transaction application, and generate a transaction identifier UID(i)={Name(i), Type(i), Quantity(i), Price(i), Asset(i), Margin(i), Time(i), Account(i)} for each transaction application; where i is the sequential number of each transaction identifier, i=1, 2, ..., n; n is the total number of transaction identifiers.

3. A secure transaction matching method under a delivery service platform according to claim 1, characterized in that: The specific process of identity consistency verification is as follows: Get the user name and trading account in the transaction identifier, obtain the historical authentication record of the user name from the database, and check whether the trading account currently submitting the request is consistent with the historical record; If the user has not undergone identity authentication in the platform or there is an abnormality in the account information, an identity authentication alarm will be triggered and the transaction request will be terminated; if the trading account corresponding to the user name has multiple login failures, the user will be required to re-authenticate.

4. A secure transaction matching method under a delivery service platform according to claim 1, characterized in that: The specific process of transaction application time verification is as follows: The transaction application time is extracted from the transaction identifier, and the number of transaction requests initiated by the same user name in each preset time interval is counted, which is recorded as the user's operation frequency in each preset time interval; if the user's operation frequency in the previous preset time interval exceeds the preset threshold, the time verification alarm is triggered and the transaction request is terminated.

5. A secure transaction matching method under a delivery service platform according to claim 1, characterized in that The specific process of fund verification is as follows: Extract the trading account from the trading identifier, query the balance in the account, and ensure that the account balance in the user's trading account is greater than the preset minimum margin amount, otherwise trigger the fund verification alarm and terminate the transaction request.

6. A secure transaction matching method under a delivery service platform according to claim 1, characterized in that: The specific process of calculating the matching degree between a transaction request and other transaction identifiers is as follows: Obtain the transaction type symbol, underlying asset number symbol, transaction quantity, price, and transaction application time corresponding to the transaction request data in each transaction application, and record them as Type (0), Asset (0), Quantity (0), Price (0), and Time (0), respectively; For the transaction type identifier, obtain the specific value of Type (0) in the transaction application; obtain the transaction identifiers corresponding to all transaction applications on all delivery service platforms except this transaction application, and extract Type (i), i = 1, 2, 3, ..., n; traverse all Type (i), calculate the result Strategy (i) of Type (0) + Type (i); the specific value of Strategy (i) represents the matching rule between the transaction identifier of this transaction application and the transaction identifier i; Provide each user with a browsing and retrieval window through the UI interface, allowing them to choose to view other transaction types that match their current transaction application according to their own wishes; Obtain the transaction identifiers corresponding to all transaction applications on all delivery service platforms except for this transaction application, based on the asset identifier, transaction quantity, price and transaction application time, and extract the transaction quantity Quantity (i), asset identifier Asset (i), price Price (i) and transaction application time Time (i); By preset formula Calculate the target object matching score P0(i); By preset formula Calculate the quantity matching score P1(i), price matching score P2(i) and transaction application time matching score P3(i); calculate the matching degree Match(i) between this transaction application and transaction identifier i through the preset formula Match(i)=P0(i)×{K1×P1(i)+K2×P2(i)+K3×P3(i)}.

7. A secure transaction matching method under a delivery service platform according to claim 6, characterized in that: The specific process of supporting users to browse and filter transactions that meet their needs through the UI interface is as follows: The UI interface provides each user with a browsing and search window, allowing them to choose to view other transaction identifiers that meet the matching degree, transaction quantity, price and transaction application time range according to their own wishes, and provides a window to sort these search results in ascending or descending order; the UI interface provides the setting of the numerical range of each search parameter, as well as the choice of whether to sort in ascending or descending order, so as to personalize transaction screening and recommendation.

8. A secure transaction matching method under a delivery service platform according to claim 1, characterized in that: The specific process of calculating the transaction risk characteristic value is as follows: After the user selects the transaction object and completes a transaction match, further information about both parties is obtained, including the number of all transaction matches c1 and c2 completed by both parties within the set time window T, and the final price of the transaction match. and the final transaction quantity ; Get the average transaction price of the asset ID matched in this transaction on the delivery service platform, and record it as the market price ; Get the average transaction quantity of the asset ID symbol Asset matched in this transaction on the delivery service platform in each transaction match, and record it as the market average transaction quantity ; Through the preset formula Calculating transaction frequency score , Transaction Price Rating and transaction quantity score ;in This is the matching frequency characteristic value of the two parties in this transaction matching; is the standard reference value for matching frequency characteristic values; Where α is the preset adjustment factor; By preset formula Calculate the risk characteristic value Risk of this transaction match; w1, w2 and w3 are preset scoring weights, and the specific numerical values ​​of the scoring weights are set according to the platform's risk tolerance and risk prevention strategy.

9. A secure transaction matching system under a delivery service platform, comprising a transaction request receiving and encryption module, a database, a transaction security cross-verification module, a sorting and recommendation module, a transaction scoring and anomaly detection module and an identity authentication and security module, characterized in that: A method for secure transaction matching under a delivery service platform for implementing any one of claims 1 to 8; The transaction request receiving and encryption module obtains basic information from the transaction application submitted by the user, including user name, transaction type, quantity, price, underlying asset number, margin amount, time and transaction account; generates a unique transaction identifier for each transaction application, including all transaction request information; uses the AES symmetric encryption algorithm to encrypt the transaction request data to ensure the confidentiality and non-tamperability of the data during storage and transmission; The encrypted transaction identifier is stored in the database to ensure the security of transaction data; The database saves all transaction identifiers and all user identity information and stores them in encrypted form; The transaction security cross-verification module ensures the legitimacy of the account submitting the request by comparing the account in the transaction request with the historical identity authentication records stored in the database; analyzes the transaction frequency of the user in different time intervals, identifies abnormal behavior of frequently submitting transaction requests, and prevents malicious manipulation; checks the balance in the user's transaction account to ensure that the account balance is greater than or equal to the minimum margin required for the transaction; The sorting and recommendation module calculates transaction matching rules based on transaction type identifiers, subject matter number identifiers and other parameters, matches transaction applications with other transaction identifiers based on the rules, and calculates the matching degree between transaction applications and other transactions through a preset matching formula; provides users with a visual interactive interface, allowing users to filter transaction objects based on transaction matching degree, price, quantity, etc., and select matching rules based on personal needs; The transaction scoring and anomaly detection module calculates transaction frequency, price, quantity and other indicators through a preset scoring formula, and gives a comprehensive score for both parties to the transaction. Based on data such as transaction frequency score, price score, quantity score, etc., the risk characteristic value of the transaction is obtained through weighted calculation; If the risk score exceeds the preset threshold, it is considered a high-risk transaction; The authentication and security module is equipped with a facial recognition camera, fingerprint recognition unit, and SMS verification unit for multi-factor authentication; When a transaction is judged to be high risk, the user is required to verify it through multiple authentication methods such as SMS verification code, facial recognition or fingerprint recognition.

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