Intelligent IC card data detection method and system
By constructing a user consumption information database and generating an integrated verification and change password, combined with a user behavior data model, the IC card payment verification process is dynamically adjusted, solving the problems of fraudulent use and tampering, and achieving an efficient and secure payment process.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-05
- Publication Date
- 2026-03-10
AI Technical Summary
Existing smart IC cards are susceptible to fraudulent use and illegal tampering during the payment process, resulting in cumbersome payment procedures, slow response times, and high costs.
By building a user consumption information database, generating integrated passwords for change and verification, combining user behavior data models, dynamically adjusting the verification process, and using card readers and terminal devices to achieve risk assessment and verification, the payment process is simplified.
It simplifies the payment verification process for IC cards, improves payment efficiency, reduces risks, and ensures payment security and response speed.
Smart Images
Figure CN121637584A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data security technology, and in particular to a smart IC card data detection method and system. Background Technology
[0002] As a device with special identity verification and information storage, the smart IC card is used to read and write IC card information through a card reader, thereby realizing digital information management, security verification, and mobile payment.
[0003] Currently, IC cards are widely used in supermarkets, schools, and public transportation. By binding IC cards to user identity information and reading / writing stored information, convenient mobile payments are achieved. However, current IC card security is mainly affected by theft and illegal tampering. The former is primarily addressed by implementing payment verification processes, but this makes the entire payment process more cumbersome and can hinder payments in high-frequency usage locations. The latter relies on complex encryption methods and data verification schemes. During a transaction, the IC card information is first compared with the terminal's key, and payment is only confirmed after successful comparison. This results in slow payment response times and high verification costs. To address these issues, a smart IC card data detection method and system are provided. Summary of the Invention
[0004] The purpose of this invention is to provide a smart IC card data detection method and system to solve the problems mentioned in the background art.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a smart IC card data detection method, comprising the following steps: S1. Read the user's IC card using a card reader to retrieve user information; S2. Enter the consumption amount and request the terminal to change the IC card amount; S3. The card reader packages the changed amount and stored value, generates an integrated password for both change and verification, and the terminal verifies the password information. S4. The terminal judges the risk of fraudulent transactions based on user behavior data and automatically requests additional verification processes based on the risk value. S5. The terminal outputs a deduction or freeze signal based on the verification result.
[0006] Preferably, in step S1, user information is obtained by binding and filing user IC card information to achieve initial basic information acquisition. At the same time, during the user IC card usage period, a user debit information database is automatically generated based on each consumption and stored value behavior. Based on the user debit information database, a user behavior data model is constructed to provide a data basis for IC card fraud risk assessment when subsequent user debit actions occur.
[0007] Preferably, the user IC card information binding and filing includes user information, IC card factory hardware identity information, and user card activation time, and generates uniquely identifiable IC card identity information through data encryption.
[0008] Preferably, the user consumption and stored value information database records each user's consumption and stored value data, including the amount and location. The location is represented by the coordinates of the card reader used to record the consumption and stored value behavior. At the same time, through long-term tracking and analysis, the user's single consumption amount range, consumption time habits and consumption frequency can also be obtained based on the consumption and stored value behavior records, thereby obtaining a behavioral data model based on each user's consumption and stored value characteristics.
[0009] Preferably, during the value storage process, a pre-registered card reader is used for identification. The stored value information is generated by synchronous pairing between the IC card and the terminal, and the stored value information is stored in the user's debit information database for data comparison and verification when subsequent debit actions occur. When a consumption action occurs, a verification and modification password is generated based on the user's debit information database to verify the correctness of the IC card amount and prevent the tampering of the amount. The correctness of the IC card consumption action is verified based on the user behavior data model to prevent fraudulent transactions.
[0010] Preferably, in step S3, the integrated password for changing and verifying the transaction reads the existing stored value information of the IC card and the input transaction amount information through the local card reader, and then packages them into an integrated password and uploads it to the terminal device. The terminal decodes the integrated password and directly verifies the stored value information. If the stored value information is consistent with the information in the user's stored value information database, a deduction confirmation signal is directly issued based on the calculated value of the integrated password; if the stored value information is inconsistent with the information in the user's stored value information database, an IC card freeze signal is directly issued, thereby simplifying the transaction verification process.
[0011] Preferably, step S4 is a synchronous processing flow based on step S3. It analyzes the risk of this transaction through a user behavior data model. The risk includes abnormal consumption amount, abnormal consumption location, and abnormal consumption frequency in a short period of time. Then, by setting a risk control model, when the risk control model threshold is reached, a further verification process is automatically triggered. This process may include quick verification methods with unique identification, such as fingerprints, facial recognition, and mobile phone verification codes, thereby preventing fraudulent transactions.
[0012] Preferably, the calculation formula for the risk control model is: ;in Indicates the degree of abnormal deviation in the amount spent; Indicates the degree of abnormal deviation from the location of consumption; Indicates the degree of abnormal deviation in short-term consumption frequency; , representing the proportionality coefficients of the three in the risk control model, is used to convert the dimensional deviation of specific behaviors into dimensionless risk coefficients, and ; Meanwhile, in the calculation model, attention is paid to the periodicity of the amount and frequency. Periodic deviations in amount and frequency are recorded as special consumption habits of users.
[0013] Preferably, the abnormal deviation of the consumption amount is calculated using normal distribution Z-score standardization, which converts the amount deviation into a deviation degree, and the calculation formula is as follows; ,in This represents the average spending amount; This indicates the amount spent this time, and the final calculation is as follows: ; The abnormal deviation of the consumption location is determined by constructing a basic consumption area distribution map based on the user's daily consumption location coordinates. Then, the point with the highest consumption frequency on the area distribution map is taken as the user's consumption center point, and then the points are arranged radially outward. When the user's consumption location exceeds the range of the area distribution map, the deviation is calculated based on the number of consuming points within the distance range. The formula is as follows: , where n represents the difference in the number of actual transaction points outside the regional distribution map compared to the nearest point within the regional distribution map, thus measuring the deviation of the consumption location. ; The short-term consumption frequency anomaly deviation is calculated based on the ratio of the long-term average number of user consumptions to the number of consumptions within the target calculation period, and the formula is as follows: ,in This represents the average daily consumption frequency of users. The average frequency of transactions over a fixed period prior to the occurrence of the transaction is used to determine whether the IC card has been used for high-frequency abnormal fraudulent transactions.
[0014] A smart IC card data detection system, comprising: The read / write module includes a card reader for consumption and stored value, which reads data from the IC card and writes data to the stored value. The local data processing module includes a core data processing and computing program embedded inside the card reader. When a debit or credit transaction occurs, it is used to package and process the basic information of the IC card, the stored value information of the IC card, and the transaction amount change information of the IC card to form an integrated password for verification and change. The communication module includes a signal transceiver module installed in the card reader, which enables data interaction with the terminal device via wireless communication; The storage module includes a terminal storage server, which is used to store user consumption information databases and encapsulate user behavior data models; The intelligent engine provides computing power for user behavior data modeling and data analysis; The intelligent terminal is used to parse and identify the integrated verification and conversion password uploaded by the card reader, and at the same time connects to the user's data storage information database and user behavior data model to realize data control and execution command issuance.
[0015] The technical effects and advantages of this invention are as follows: This smart IC card data detection method addresses existing IC card risks by simplifying the IC card information verification process and dynamically adjusting the payment verification scheme. From the moment a user acquires the IC card until each payment transaction, a user's stored value information database is automatically generated and stored. Simultaneously, a user behavior data model is constructed based on this database. During subsequent payments, the card reader generates an integrated verification and modification password based on the stored value, user information, and deduction amount, sending it to the terminal. The terminal compares the stored value with the data to mitigate IC card balance tampering risks. Furthermore, it compares the user's current payment information with the user behavior data model, selectively activating further verification processes based on risk level. Upon confirmation, a balance modification password or freeze is directly issued, and the card reader executes the IC card balance change or freeze action. This simplifies the payment process, improves efficiency, and reduces payment risks. Attached Figure Description
[0016] Figure 1 This is a logical framework diagram of the smart IC card data detection method of the present invention; Figure 2 This is a basic flowchart of the smart IC card data detection method of the present invention; Figure 3 This is a detailed flowchart of the smart IC card data detection method of the present invention; Figure 4 This is a functional architecture diagram of the smart IC card data detection system of the present invention. Detailed Implementation
[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] Example 1: This embodiment of the invention provides, as follows Figures 1-3 The smart IC card data detection method shown includes the following steps: S1. Read the user's IC card using a card reader to retrieve user information; S2. Enter the consumption amount and request the terminal to change the IC card amount; S3. The card reader packages the changed amount and stored value, generates an integrated password for both change and verification, and the terminal verifies the password information. S4. The terminal judges the risk of fraudulent transactions based on user behavior data and automatically requests additional verification processes based on the risk value. S5. The terminal outputs a deduction or freeze signal based on the verification result.
[0019] Preferably, in step S1, user information is obtained by binding and filing user IC card information to achieve initial basic information acquisition. At the same time, during the user IC card usage period, a user debit information database is automatically generated based on each consumption and stored value behavior. Based on the user debit information database, a user behavior data model is constructed to provide a data basis for IC card fraud risk assessment when subsequent user debit actions occur.
[0020] Preferably, the user IC card information binding and filing includes user information, IC card factory hardware identity information, and user card activation time, and generates uniquely identifiable IC card identity information through data encryption.
[0021] Preferably, the user consumption and stored value information database records each user's consumption and stored value data, including the amount and location. The location is represented by the coordinates of the card reader used to record the consumption and stored value behavior. At the same time, through long-term tracking and analysis, the user's single consumption amount range, consumption time habits and consumption frequency can also be obtained based on the consumption and stored value behavior records, thereby obtaining a behavioral data model based on each user's consumption and stored value characteristics.
[0022] Preferably, during the value storage process, a pre-registered card reader is used for identification. The stored value information is generated by synchronous pairing between the IC card and the terminal, and the stored value information is stored in the user's debit information database for data comparison and verification when subsequent debit actions occur. When a consumption action occurs, a verification and modification password is generated based on the user's debit information database to verify the correctness of the IC card amount and prevent the tampering of the amount. The correctness of the IC card consumption action is verified based on the user behavior data model to prevent fraudulent transactions.
[0023] Preferably, in step S3, the integrated password for changing and verifying the transaction reads the existing stored value information of the IC card and the input transaction amount information through the local card reader, and then packages them into an integrated password and uploads it to the terminal device. The terminal decodes the integrated password and directly verifies the stored value information. If the stored value information is consistent with the information in the user's stored value information database, a deduction confirmation signal is directly issued based on the calculated value of the integrated password; if the stored value information is inconsistent with the information in the user's stored value information database, an IC card freeze signal is directly issued, thereby simplifying the transaction verification process.
[0024] Preferably, step S4 is a synchronous processing flow based on step S3. It analyzes the risk of this transaction through a user behavior data model. The risk includes abnormal consumption amount, abnormal consumption location, and abnormal consumption frequency in a short period of time. Then, by setting a risk control model, when the risk control model threshold is reached, a further verification process is automatically triggered. This process may include fingerprint, facial recognition, and mobile phone verification code, which are unique and quick verification methods, thereby preventing fraudulent transactions.
[0025] Preferably, the calculation formula for the risk control model is: ;in Indicates the degree of abnormal deviation in the amount spent; Indicates the degree of abnormal deviation from the location of consumption; Indicates the degree of abnormal deviation in short-term consumption frequency; , representing the proportionality coefficients of the three in the risk control model, is used to convert the dimensional deviation of specific behaviors into dimensionless risk coefficients, and ; Meanwhile, in the calculation model, attention is paid to the periodicity of the amount and frequency. Periodic deviations in amount and frequency are recorded as special consumption habits of users.
[0026] Preferably, the abnormal deviation of the consumption amount is calculated using the normal distribution Z-score standardization, which converts the amount deviation into the deviation degree. The calculation formula is as follows: ,in This represents the average spending amount; This indicates the amount spent this time, and the final calculation is as follows: ; The abnormal deviation of the consumption location is calculated by constructing a basic consumption area distribution map based on the user's daily consumption location coordinates. Then, the point with the highest consumption frequency on the area distribution map is taken as the user's consumption center point, and then the points are arranged radially outward. When the user's consumption location is outside the range of the area distribution map, the deviation is calculated according to the number of consuming points within the distance range. The formula is as follows: , where n represents the difference in the number of actual transaction points outside the regional distribution map compared to the nearest point within the regional distribution map, thus measuring the deviation of the consumption location. ; The short-term consumption frequency deviation is calculated based on the ratio of the long-term average number of user consumptions to the number of consumptions within the target calculation period, and the formula is as follows: ,in This represents the average daily consumption frequency of users. The average frequency of transactions over a fixed period prior to the occurrence of the transaction is used to determine whether the IC card has been used for high-frequency abnormal fraudulent transactions.
[0027] Working principle: This method addresses the risks associated with existing IC cards by simplifying the IC card information verification process and dynamically adjusting the payment verification scheme. From the moment a user acquires an IC card, the method binds and files the user and IC card information based on user information, the IC card's factory hardware identity information, and the user's card activation time. Simultaneously, during the user's IC card usage period, a user debit / credit information database is automatically generated based on each transaction and debit / credit transaction. Furthermore, based on this database, a user behavior data model is constructed to provide a data foundation for assessing the risk of IC card fraud when subsequent debit / credit transactions occur. Each time a user cancels a stored value, the IC card contacts the card reader, initiating the payment process. The card reader then reads the stored value and user information from the IC card. The user then enters the deduction amount and clicks "Confirm Deduction." At this point, the card reader generates a verification and modification password based on the stored value, user information, and deduction amount, sending it to the terminal. The terminal then compares the changed IC card balance with the user's stored value database. By checking if the amounts match, the terminal determines if the IC card balance has been tampered with. If a discrepancy is found, a card freeze password is issued directly to the card reader, terminating the payment. The payment function of the IC card is restricted. If the amounts are equal, it means that there is no tampering of the amount. At this time, the amount, payment point coordinates and recent payment frequency in the characteristics of this payment behavior are compared with the user behavior data model. The fraud risk level is output according to the comparison result. When the fraud risk value reaches the threshold, the verification process is automatically triggered. At this time, the inherent matching information between the user and the IC card can be verified through pre-written user information (including but not limited to password, fingerprint, face or other verification methods). If the match is successful, the amount change password is automatically issued. If the match is unsuccessful, the IC card is frozen. Traditional verification processes require verifying IC card information before proceeding to payment. In contrast, this solution embeds the payment process into the verification process, simplifying both and improving payment response speed. Simultaneously, based on the integrated verification and change password, the data characteristics of the payment behavior are uploaded synchronously, enabling risk assessment. This risk assessment then triggers further verification processes, ensuring payment security while improving efficiency.
[0028] Example 2: This embodiment of the invention provides, as follows Figure 4 The smart IC card data detection system shown includes: The read / write module includes a card reader for consumption and stored value, which reads data from the IC card and writes data to the stored value. The local data processing module includes a core data processing and computing program embedded inside the card reader. When a debit or credit transaction occurs, it is used to package and process the basic information of the IC card, the stored value information of the IC card, and the transaction amount change information of the IC card to form an integrated password for verification and change. The communication module includes a signal transceiver module installed in the card reader, which enables data interaction with the terminal device via wireless communication; The storage module includes a terminal storage server, which is used to store user consumption information databases and encapsulate user behavior data models; The intelligent engine provides computing power for user behavior data modeling and data analysis; The intelligent terminal is used to parse and identify the integrated verification and conversion password uploaded by the card reader, and at the same time connects to the user's data storage information database and user behavior data model to realize data control and execution command issuance.
[0029] Working Principle: This intelligent IC card data detection system modifies existing card readers by writing local data processing and calculation programs into them. This enables integrated password generation for both verification and change of payment methods. Simultaneously, an intelligent terminal is set up, and a storage module stores a database of user transaction information and encapsulates a user behavior data model. The intelligent terminal uses the integrated password to access user data from the database and model, thereby achieving IC card data verification, payment confirmation, and dynamic verification scheme execution. This allows for rapid and effective IC card verification at the payment end, enabling users to selectively verify based on risk, and simultaneously issuing payment passwords. This simplifies the payment process, improves efficiency, and reduces payment risk.
[0030] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for detecting data of an intelligent IC card, characterized by, The method comprises the following steps: S1, reading the user IC card through a card reader to call user information; S2, inputting the consumption amount and requesting the IC card amount change to the terminal; S3, the card reader packs the changed amount and the stored value amount to generate a change and verification integrated password, and the terminal verifies the password information; S4, the terminal judges the risk of stolen card according to the user behavior data and automatically requires to increase the verification process according to the risk value; S5, the terminal outputs the deduction or freezing signal according to the verification result.
2. The intelligent IC card data detection method of claim 1, wherein, In the step S1, the user information is obtained through the user IC card information binding and filing, and in the use cycle of the user IC card, the user consumption and storage information database is automatically generated according to each consumption and storage behavior, and based on the user consumption and storage information database, the user behavior data model is constructed to provide the IC card stolen card risk assessment data basis when the subsequent user consumption and storage actions occur.
3. The intelligent IC card data detection method of claim 2, wherein, The user IC card information binding and filing includes user information, IC card factory hardware identity information and user card opening time, and the IC card identity information with unique identification is generated through data encryption.
4. The intelligent IC card data detection method of claim 2, wherein, The user consumption and storage information database records the user's each consumption and storage data information, including the amount and the place, and the place is represented by the coordinates of the card reader used for consumption and storage behavior, and through long-term tracking analysis, the user's single consumption amount range, consumption time habit and consumption frequency can be obtained according to the consumption and storage behavior record analysis, so as to obtain the behavior data model based on the consumption and storage characteristics of each user.
5. The intelligent IC card data detection method of claim 2, wherein, When the user consumption and storage actions occur, including storage and consumption, the pre-filed card reader is used for identification operation in the storage process, the storage information is synchronized and paired with the data generated in the IC card and the terminal, and the storage information is left in the user consumption and storage information database for subsequent consumption and storage behavior data comparison and verification; when the consumption behavior occurs, the change and verification integrated password is generated based on the user consumption and storage information database to verify the correctness of the IC card amount and avoid the occurrence of amount tampering behavior; the user behavior data model is used to verify the correctness of the IC card consumption behavior and avoid the occurrence of stolen card behavior.
6. The intelligent IC card data detection method of claim 1, wherein, In the step S3, the change and verification integrated password reads the existing storage information of the IC card through the local card reader and inputs the transaction amount information, then packs the integrated password to upload to the terminal device, the terminal decodes and directly verifies the storage information after reading the integrated password, if the storage information is consistent with the information in the user consumption and storage information database, the deduction confirmation signal is issued based on the calculation value of the integrated password; if the storage information is inconsistent with the information in the user consumption and storage information database, the IC card freezing signal is directly issued, so as to simplify the transaction verification process.
7. The intelligent IC card data detection method of claim 6, wherein, The step S4 is a synchronization process made on the basis of step S3, which analyzes the risk of the transaction through a user behavior data model, including consumption amount anomaly, consumption location anomaly, and consumption frequency anomaly in a short period, and sets a risk control model to automatically trigger further verification procedures when the threshold of the risk control model is reached, which can include fingerprint, face, and mobile phone verification codes with unique identification for quick verification, thereby avoiding fraudulent transactions.
8. The intelligent IC card data detection method of claim 7, wherein, The calculation formula of the risk control model is: ; wherein represents the abnormal deviation degree of the consumption amount; represents the abnormal deviation degree of the consumption location position; represents the abnormal deviation degree of the short-term consumption frequency; , represents the proportion coefficient of the three in the risk control model, which is used to convert the specific behavior deviation degree with dimension into the risk coefficient without dimension, and ; Meanwhile, in the calculation model, the time periodicity problem is considered for the amount and frequency, and the periodic amount deviation and frequency deviation are recorded as the special consumption habit characteristics of the user.
9. The intelligent IC card data detection method of claim 8, wherein, The abnormal deviation degree of the consumption amount is calculated by normal distribution Z-score standardization, which converts the amount deviation into deviation degree, and the calculation formula is: Wherein represents the average consumption amount; represents the consumption amount of this time, and finally is calculated; The abnormal deviation degree of the consumption site position is constructed according to the basic consumption area distribution map of the user daily consumption site coordinates, and then the point with the highest consumption frequency in the area distribution map is taken as the user consumption center point, and then the radiation is arranged outward, when the user consumption site exceeds the range of the area distribution map, the deviation degree is calculated according to the number of consumable points within the distance range, and the formula is: Wherein n represents the point number difference between the actual transaction point outside the area distribution map and the nearest point inside the area distribution map, which measures the deviation degree of the consumption site position, and ; The short-term consumption frequency abnormal deviation degree is calculated according to the ratio of the long-term average consumption frequency of the user to the consumption frequency in the target calculation period, and the formula is: , wherein is the average daily consumption frequency of the user; is the average consumption frequency in a fixed period of time from the time of the consumption behavior to the front, and whether the IC card has a high-frequency abnormal theft behavior is determined through the feature.
10. An intelligent IC card data detection system for performing the intelligent IC card data detection method according to any one of claims 1 to 9, characterized by It includes: The read-write module includes a card reader for consumption and value storage, and the IC card data reading and value storage data writing are performed through the card reader; The local data processing module includes a core data processing calculation program implanted in the card reader, which is used to package the IC card basic information, IC card value information, and IC card transaction amount change information when the consumption and storage behavior occurs to form a change and verification integrated password; The communication module includes a signal transceiver module arranged in the card reader, which realizes data interaction with the terminal device through wireless communication; The storage module includes a terminal storage server for storing user consumption information database and encapsulating user behavior data model; The intelligent engine is used to provide computing power for user behavior data model data analysis; The intelligent terminal is used to analyze and identify the change and verification integrated password uploaded by the card reader, and connects the user consumption information database and the user behavior data model to realize data management and execution instruction issuance.