Offline payment fraud prevention system and method based on dynamic encryption technology

Abstract

The invention relates to the technical field of payment security, and discloses an offline payment fraud prevention system and method based on a dynamic encryption technology, and the system comprises a dynamic key generation module, a payment data encryption module, a payment data encryption module, a fraud detection module, and a fraud detection module. The method comprises the steps that a high-dimensional chaotic system generates a dynamic payment secret key, payment data is subjected to nonlinear topology encryption and secondary encryption, a transaction verification module decrypts and verifies legality of the payment data, a transaction verification result is generated, a fraud detection module analyzes the verification result, a fraud behavior is recognized, and a defense strategy is adjusted. The payment confirmation module judges whether payment is executed or not according to verification and detection results, and payment transaction is completed or refused. Compared with the prior art, the method has the advantages that the problems of static key multiplexing, fraud detection lagging and transaction verification incompleteness are effectively solved, the safety and protection capability of a payment system are improved, and complex payment fraud risks can be better coped with.

Description

Technical Field

[0001] The present invention relates to the technical field of payment security, and particularly to an offline payment anti-fraud system and method based on dynamic encryption technology. Background Art

[0002] With the rapid development of electronic payment technology, especially the wide application of offline payment methods, the security issue of payment systems has increasingly become the focus of attention. Traditional payment systems generally adopt static keys and encryption technology to ensure the security of transactions. However, this traditional security mechanism has significant deficiencies, especially when dealing with increasingly complex and variable payment fraud behaviors, it seems powerless.

[0003] Firstly, most existing payment systems rely on static keys to encrypt payment data. Once the static key is leaked or obtained by an attacker, a large amount of payment data may be exposed. More seriously, static keys may be reused in different transactions, which makes it easier for attackers to conduct attacks by cracking the key or predicting the encryption pattern. Therefore, traditional encryption technology has potential security risks such as key leakage and key reuse, which makes payment systems vulnerable to security threats such as man-in-the-middle attacks and replay attacks.

[0004] Secondly, existing fraud detection technologies usually rely on rule bases or simple pattern recognition to determine whether a transaction is abnormal, but these methods are often difficult to identify complex and concealed fraud behaviors in a timely manner. For example, for fraud means such as forged identities and false transactions, traditional detection methods often rely on preset rules and cannot adapt to rapidly changing attack means, resulting in problems such as detection lag and poor accuracy. This makes it difficult for payment systems to identify potential fraud risks in real time before a transaction occurs, leading to financial losses and a decline in user trust.

[0005] Furthermore, the transaction verification processes in existing payment systems are mostly relatively simple, only performing identity verification or simple transaction rule matching. For high-risk transactions, the system often lacks sufficient multiple verification mechanisms, resulting in fraud transactions being easily overlooked or passed through. Although some high-value payments or sensitive transactions may require additional identity verification, this mechanism is often overlooked in ordinary transactions, lacking all-round risk control and being difficult to effectively prevent the occurrence of situations such as account theft and malicious payments.

[0006] In addition, existing encryption technologies generally adopt linear or symmetric encryption methods, which show certain deficiencies in protecting data privacy and security. Especially when facing advanced cracking technologies, they are vulnerable to attacks and lead to data leakage. Although the encryption strength has been improved, most traditional encryption technologies still have key management problems and do not have sufficient countermeasures in preventing replay attacks, data tampering, etc.

[0007] Therefore, the present invention proposes an offline payment anti-fraud system and method based on dynamic encryption technology to solve the deficiencies of the prior art. Summary of the Invention

[0008] In view of the deficiencies of the prior art, the present invention provides an offline payment anti-fraud system and method based on dynamic encryption technology, which solves the problems of easy leakage of static keys, lag in fraud detection, and imperfect transaction verification mechanism.

[0009] To achieve the above objectives, the present invention is realized through the following technical solutions: An offline payment anti-fraud system based on dynamic encryption technology, comprising: A dynamic key generation module, configured to generate a dynamic payment key in real time according to a high-dimensional chaotic system, and generate a unique and non-repeating dynamic payment key for each transaction; A payment data encryption module, configured to perform non-linear topological encryption on payment data, and encrypt the encrypted data in combination with the dynamic payment key provided by the dynamic key generation module; A transaction verification module, configured to decrypt and verify the encrypted payment data, and determine whether it is a legal transaction, and generate a transaction verification result; A fraud detection module, configured to detect whether there is a fraud risk based on the transaction verification result, generate a fraud detection result, and adjust the defense strategy according to the fraud detection result; A payment confirmation module, configured to decide whether to complete the payment transaction according to the fraud detection result and the transaction verification result.

[0010] Preferably, the dynamic payment key is only valid in the current transaction, and no preset or long-term stored static payment key is required during the generation process, thereby improving the randomness of the key and the security of the payment transaction.

[0011] Preferably, the high-dimensional chaotic system is composed of multiple iteration equations, and the iteration equations are: ; Wherein, is the state variable of the high-dimensional chaotic system at the th iteration; is the state variable of the system at the th iteration; is the control parameter of the chaotic system, which is a preset real constant; is the discrete time step.

[0012] Preferably, the payment data encryption module includes: A data preprocessing module, configured to format and standardize payment data; Nonlinear topological encryption module, used for nonlinearly topologically encrypting payment data; Dynamic key encryption module, used for secondarily encrypting the encrypted data in combination with a dynamic payment key.

[0013] Preferably, the steps for nonlinearly topologically encrypting the payment data are as follows: Perform block processing on the payment data, dividing the payment data into multiple data blocks; Perform a nonlinear transformation on each data block, mapping the data block using a chaotic function; After subjecting each data block to a topological transformation, merge them; Encrypt the merged data blocks, and further encrypt using a dynamic payment key.

[0014] Preferably, the steps for secondarily encrypting the encrypted data in combination with a dynamic payment key are as follows: Obtain the generated dynamic payment key; Perform an exclusive OR operation on the encrypted data using the dynamic payment key; Perform further encryption processing on the result of the exclusive OR operation to ensure the non-readability of the data; Output the finally encrypted payment data.

[0015] Preferably, the transaction verification module includes: Data decryption module, used for decrypting the encrypted payment data; Legitimacy verification module, used for verifying whether the decrypted payment data conforms to the predetermined transaction rules; Transaction verification result generation module, used for generating a legitimacy transaction verification result and judging whether the transaction is valid.

[0016] Preferably, the fraud detection module includes: Risk assessment module, used for assessing the transaction risk according to the transaction verification result; Fraud behavior identification module, used for detecting whether there is an abnormal transaction pattern; Fraud detection result generation module, used for generating a fraud detection result according to the outputs of the risk assessment module and the fraud behavior identification module; Risk adjustment module, used for adjusting the defense strategy according to the fraud detection result.

[0017] Preferably, the payment confirmation module includes: Fraud detection result judgment module, used for judging whether there is a risk in the transaction according to the fraud detection result; Transaction verification result judgment module, used for judging whether the transaction is legal according to the transaction verification result; A payment execution module, which is used to execute payment operations when the transaction is legal and there is no fraud risk.

[0018] The present invention also provides an offline payment anti-fraud method based on dynamic encryption technology, including the following steps: Generate a dynamic payment key corresponding to the current transaction based on a high-dimensional chaotic system through a dynamic key generation module; Perform non-linear topological encryption on payment data through a payment data encryption module, and perform secondary encryption on the encrypted data in combination with the dynamic payment key; Decrypt and verify the legality of the encrypted payment data through a transaction verification module to generate a transaction verification result; Analyze the transaction verification result through a fraud detection module to identify whether there is fraud, generate a fraud detection result and adjust the defense strategy; Judge whether to execute the payment according to the transaction verification result and the fraud detection result through a payment confirmation module, and complete the payment transaction or refuse to execute.

[0019] The present invention provides an offline payment anti-fraud system and method based on dynamic encryption technology. It has the following beneficial effects: 1. The present invention adopts the technical solution of generating dynamic payment keys based on a high-dimensional chaotic system. By generating unique and non-repeating keys for each transaction, it greatly improves the security of transactions. Compared with the existing static key technology, static keys are vulnerable to attacks and the risk of reuse. The present invention effectively avoids this security hidden danger, making each transaction highly unpredictable and anti-cracking.

[0020] 2. The present invention improves the security of payment data through the secondary encryption scheme of combining non-linear topological encryption and dynamic payment keys by the payment data encryption module. Different from the existing encryption technology, the present invention prevents data from being tampered with or stolen during transmission through double encryption and the introduction of chaotic algorithms, ensuring the confidentiality and integrity of payment data.

[0021] 3. Realize real-time evaluation and dynamic adjustment of transaction risks through the fraud detection module. Through multi-dimensional analysis and abnormal pattern recognition, potential fraud behaviors can be discovered in a timely manner. Compared with traditional rule-based detection systems, the present invention adopts a more intelligent evaluation mechanism, which can more accurately identify complex fraud behaviors and ensure that the protection of the payment system is more comprehensive and efficient.

[0022] 4. Introduce a multi-layer verification mechanism and a payment confirmation module to conduct strict identity verification and risk confirmation before the transaction is executed, ensuring that the payment is legal and there is no fraud risk. Different from the simple confirmation process in the existing payment system, the present invention further strengthens the security of payment confirmation by combining external authentication systems, device information and other factors, effectively avoiding the risks of false payment and account theft. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is the system architecture diagram of the present invention; Figure 2 is the architecture diagram of the payment data encryption module of the present invention; Figure 3 is the architecture diagram of the transaction verification module of the present invention; Figure 4 is the architecture diagram of the fraud detection module of the present invention; Figure 5 is the architecture diagram of the payment confirmation module of the present invention; Figure 6 is the method flow chart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] Please refer to the attached Figure 1 - attached Figure 5 , the embodiment of the present invention provides an offline payment anti-fraud system based on dynamic encryption technology, including: A dynamic key generation module, configured to generate a dynamic payment key in real time according to a high-dimensional chaotic system, and generate a unique and non-repeating dynamic payment key for each transaction; The dynamic key generation module generates a dynamic payment key in real time based on a high-dimensional chaotic system. A unique and non-repeating dynamic payment key is generated for each transaction to ensure that the key for each transaction is completely different from other transactions, thereby improving the security of the system and effectively preventing the security risks brought by key reuse. Specifically, the dynamic key generation module generates a new and independent key at the beginning of each transaction, and this key becomes invalid after the current transaction is completed and is no longer used for subsequent transactions.

[0026] In this embodiment, the dynamic key generation module generates the dynamic payment key through a high-dimensional chaotic system. The core idea of the high-dimensional chaotic system is to generate a highly irregular and unpredictable key through the non-linear coupling of multiple variables and a complex iterative process. By introducing a high-dimensional chaotic algorithm, the key generated each time has no correlation with the past keys, greatly improving the security.

[0027] In general, a high-dimensional chaotic system includes multiple interrelated iterative equations, and these equations are used to iteratively update multiple state variables. For each transaction, the system generates a new key in real time through the high-dimensional chaotic system based on the current state variables. At each transaction, the dynamic payment key changes under the control of the high-dimensional chaotic system, so the key generated each time is unique, unpredictable, and cannot be reused.

[0028] As an option, the iterative equations used in the high-dimensional chaotic system can be defined as follows: ; where, is the state variable of the high-dimensional chaotic system at the th iteration; is the state variable of the system at the th iteration; is the control parameter of the chaotic system, which is a preset real constant; represents the discrete time step. The iterative equation is updated through the non-linear coupling of these variables and the control parameter, thereby generating a new state variable.

[0029] Specifically, the parameters in the above equation are the control parameters of the high-dimensional chaotic system. These parameters are preset during system initialization and can be adjusted according to specific application scenarios. Their values are usually between 0 and 1. Different control parameters will result in different key generation patterns, so by adjusting these control parameters, the unpredictability of the key generation process can be further increased.

[0030] In a possible implementation, assume that are four variables representing the current state respectively, and are the control parameters of the system respectively. According to these state variables and control parameters, the iterative equation will generate a new state each time, thereby obtaining a new dynamic payment key.

[0031] The result of each iterative update is jointly determined by the state variables at the previous moment and the system control parameters. Therefore, the high-dimensional chaotic system has strong sensitivity, and any small change will lead to different final keys. This feature makes the dynamic payment key generated for each transaction highly uncertain and secure.

[0032] In some embodiments, in order to further enhance the security of the system, the dynamic key generation module can generate the final dynamic payment key by introducing multiple high-dimensional chaotic systems and combining their outputs. This can increase the complexity of the system and further reduce the possibility for attackers to obtain the key through prediction or reverse engineering.

[0033] In another embodiment, the dynamic key generation module can adjust the initial state of the high-dimensional chaotic system by combining external information such as user identity information and transaction data, so that the key generation process for each user or each transaction is more personalized. In this way, even for the same system and control parameters, the keys for different users or different transactions will be significantly different.

[0034] In some cases, to enhance the flexibility of the system, the dynamic key generation module can also dynamically adjust the control parameters of the chaotic system , to cope with different attack threats. For example, when a certain type of attack is detected, the system can automatically modify the control parameters, causing the output of the chaotic system to change, further enhancing the unpredictability and security of the key.

[0035] Through this dynamic key generation method based on the high-dimensional chaotic system, the present invention significantly improves the key security in the payment process. Different, unique and unpredictable dynamic keys are generated for each transaction, reducing the risk of key leakage or reuse. This method not only ensures the security of each transaction, but also avoids the problems of static key leakage or cracking that may occur in traditional systems.

[0036] Generally speaking, by introducing the high-dimensional chaotic algorithm for dynamic key generation, the system can provide stronger security guarantees in the ever-changing payment scenarios, fully protecting every step of the payment process. This technical method can effectively prevent attacks on the payment system through means such as brute force cracking, further enhancing the anti-attack ability of the payment system.

[0037] A payment data encryption module, which is used to perform non-linear topological encryption on payment data and encrypt the encrypted data with the dynamic payment key provided by the dynamic key generation module; The main function of the payment data encryption module is to encrypt payment data to prevent the data from being tampered with, stolen or forged during the transmission process. The encryption process not only involves non-linear topological encryption, but also combines the dynamic payment key provided by the aforementioned dynamic key generation module to perform secondary encryption on the encrypted data. Through this dual encryption mechanism, the system can effectively enhance the security of payment data and prevent malicious attackers from cracking by analyzing the encrypted data.

[0038] In this embodiment, the payment data encryption module first performs formatting and normalization processing on the payment data through the data preprocessing module to ensure that the input data conforms to the format expected by the system and is convenient for subsequent processing. The formatted data will enter the non-linear topological encryption module, which uses the chaotic algorithm to perform non-linear transformation on the payment data. Through non-linear topological encryption, the structure of the data is deeply confused, thus greatly increasing the complexity of the data, making the data almost unpredictable and enhancing the security of the data.

[0039] In general, the non - linear topology encryption module divides the payment data into multiple data blocks and performs non - linear transformation on each data block. Through the mapping of the chaotic function, the original form of the payment data block is converted into a complex encryption structure. Specifically, the encryption process of each data block uses a high - dimensional chaotic function, based on the state variables and control parameters of the system, to ensure that the output result of each encryption has a high degree of irregularity.

[0040] As an option, during the encryption process, the input of the chaotic function includes not only the payment data block itself but also the random variables of the current state of the system. In this way, even the same payment data will generate completely different encryption results in different transactions. This method further increases the unpredictability and security of data encryption and avoids the predictability risk of static encryption.

[0041] Specifically, during this encryption process, the payment data is split into several blocks, and each block of data is encrypted separately. After each data block is mapped by the chaotic function, there is no linear relationship between it and other blocks, which makes the data structure more complex. The introduction of the chaotic algorithm makes the encryption result of each data block almost impossible to follow a pattern, enhancing the system's ability to resist brute - force cracking attacks.

[0042] On this basis, the final encrypted result of the payment data will be further encrypted by the dynamic key encryption module. This module uses the dynamic payment key provided by the aforementioned dynamic key generation module to further encrypt the already encrypted payment data. The secondary encryption uses methods such as exclusive - OR operation to transform the encrypted data, ensuring that the finally generated encrypted data is more secure and cannot be cracked or stolen during transmission.

[0043] In one possible implementation, the dynamic payment key is combined with the already encrypted data through exclusive - OR operation. This process can be achieved through the following formula: ; where, represents the data after the first encryption; represents the dynamic payment key; represents the exclusive - OR operation; is the finally encrypted payment data.

[0044] In some embodiments, to increase the security of the secondary encryption, in addition to the exclusive - OR operation, other encryption algorithms such as AES encryption or RSA encryption can be combined to further process the data. This multi - level and multi - method encryption means can effectively avoid known encryption cracking methods, thus greatly enhancing the security of payment data.

[0045] In another embodiment, for different types of payment data, the payment data encryption module may adopt different encryption strategies. For example, for payment data with a large amount or high sensitivity, the system may choose to use a stronger encryption method, or increase the number and layers of encryption to meet different levels of security requirements.

[0046] Specifically, in the design of the payment data encryption module, the flexibility in different payment scenarios is also considered. For example, the payment data can be encrypted based on the identity information of the two trading parties to ensure the uniqueness of the encrypted data in different trading environments. Such an encryption strategy can avoid using the same encryption mode in different transactions and reduce the risk of the system being subject to systematic attacks.

[0047] Through the above payment data encryption process, the present invention significantly improves the security of payment data. First, through the block processing and non-linear topological encryption of the data, the high complexity of the payment data during the encryption process is ensured, making the data almost impossible to be restored. Second, the secondary encryption combined with the dynamic key increases the randomness of the encryption result, so that even if an attacker obtains some encrypted data, it cannot be effectively cracked. In addition, the introduction of the chaotic function and random state variables further enhances the unpredictability of key generation and data encryption.

[0048] The beneficial effect of this encryption method is that it not only improves the security of the encrypted data, avoids the predictability problem of traditional static encryption, but also makes the system have a strong anti-cracking ability in the face of advanced attacks through the combination of dynamically generated keys and multi-layer encryption.

[0049] In summary, the implementation method of the payment data encryption module provides a strong data protection ability for the payment system, which can not only effectively protect the confidentiality of transaction data, but also prevent the data from being tampered with and forged, providing a more secure and reliable payment environment for users.

[0050] The transaction verification module is used to decrypt, verify the encrypted payment data, determine whether it is a legal transaction, and generate a transaction verification result; The main function of the transaction verification module is to decrypt the payment data encrypted by the payment data encryption module and verify whether the transaction data meets the predetermined transaction rules and legality requirements. During the payment process, the transaction verification module plays a role in reviewing and verifying the payment data to ensure the validity of the transaction and prevent forgery and illegal transactions.

[0051] In this embodiment, the transaction verification module includes three main functional sub-modules: a data decryption module, a legality verification module, and a transaction verification result generation module. These sub-modules work together to ensure the compliance and security of payment transactions.

[0052] Under normal circumstances, after receiving the encrypted payment data, the transaction verification module first performs decryption processing. The data decryption module uses the dynamic payment key previously provided by the dynamic key generation module to decrypt the payment data. Since a unique dynamic payment key is generated for each transaction, the decryption process ensures that only the system with the correct key can successfully decrypt the data, thus avoiding the risks of key leakage or data tampering.

[0053] As an option, the data decryption module can adopt various decryption algorithms, such as AES, RSA, etc., and the specific algorithm can be flexibly selected according to needs. By using strong encryption algorithms in combination with dynamic keys, the security of the decryption process is further enhanced, ensuring that only authorized systems can decrypt the data.

[0054] Specifically, in the decryption stage, after the payment data undergoes non-linear topological encryption processing, it is transmitted in encrypted form. The data decryption module uses the dynamic key to decrypt the data and restore the encrypted payment data to its original state. The core of this process is that the uniqueness and correctness of the decryption process depend on the correctness of the dynamic key, avoiding the problems of key reuse and leakage that may exist in traditional static key encryption.

[0055] In a possible implementation, the data decryption module decrypts the data through the following formula: ; where, represents the decrypted data; represents the encrypted data; represents the exclusive OR operation, is the dynamic payment key. This formula shows that in each payment transaction, the decryption module uses a unique dynamic key to decrypt the encrypted data to ensure the security of the data.

[0056] In some embodiments, the data decryption module not only depends on the dynamic key but may also be combined with other factors such as timestamps. This can further ensure the independence and unpredictability of the decryption process. Specifically, the system can set a time window within which the same dynamic key is used for decryption processing, which avoids the possibility of the key being obtained in advance and used in other time periods.

[0057] After the data is decrypted, the legitimacy verification module will verify the legitimacy of the decrypted payment data. The verification content includes whether the payment amount, the information of the payer and the payee comply with the predetermined transaction rules. Specifically, the legitimacy verification module will judge whether the transaction meets the requirements by comparing the relevant information in the payment data with the preset transaction rules (for example, amount limit, identity matching of both parties in the transaction, etc.). If any field in the data does not meet the requirements, the legitimacy verification module will mark the transaction as an invalid transaction.

[0058] In another embodiment, the legitimacy verification module will execute different levels of verification rules according to different transaction types. For example, for large-value payments or sensitive transactions, the system may require more stringent verification procedures, such as multi-factor authentication or secondary confirmation. Such verification measures can enhance the system's auditing ability for special transactions and ensure the compliance of the payment process.

[0059] Specifically, the legitimacy verification module judges the legitimacy of the transaction through the following formula: ; where represents the legitimacy verification function, represents the transaction amount, and represent the identity information of the payer and the payee respectively, represents the transaction time, represents other factors that may affect the legitimacy.

[0060] As an option, the legitimacy verification module can evaluate the compliance of transactions based on artificial intelligence or machine learning technologies. For example, by learning historical transaction data, the system can identify abnormal transaction patterns and automatically generate warnings or perform rejection operations when detecting abnormal transaction behaviors.

[0061] The transaction verification result generation module is responsible for generating the final transaction verification result based on the decryption and verification results. This module will judge whether the transaction is valid according to the output of the legitimacy verification module. If the transaction meets all verification rules, the system will generate a verification result of "legitimate transaction" and allow the transaction to continue. If the transaction is determined to be illegal or abnormal, the system will generate an "invalid transaction" result and reject the payment request.

[0062] In some embodiments, the transaction verification result generation module may feedback the verification result and detailed error information to the user or the relevant payment institution so that they can take measures to handle abnormal transactions in a timely manner. The system can also generate detailed log records for subsequent auditing and risk assessment.

[0063] Through the design of the above transaction verification module, the system can effectively verify the legality of payment transactions and ensure the effectiveness of transactions. The decryption of each payment data depends on a dynamically generated key, ensuring data security and preventing unauthorized access. In addition, the legality verification module can perform multiple verifications on transactions based on preset transaction rules, further preventing the occurrence of illegal transactions.

[0064] Generally speaking, the transaction verification module not only enhances the security of the system but also ensures the compliance of transactions, enabling the system to respond promptly in the face of potential fraud. Through an efficient decryption and verification mechanism, the transaction verification module provides a reliable guarantee for the payment system, enhancing users' trust and payment experience.

[0065] A fraud detection module, used to detect whether there is a fraud risk based on the transaction verification result, generate a fraud detection result, and adjust the defense strategy according to the fraud detection result; The main function of the fraud detection module is to detect potential fraud by analyzing the verification results of payment transactions and dynamically adjust the system's defense strategy based on this result. Through multiple data analyses, behavior pattern recognition, and real-time risk assessment, the fraud detection module can promptly identify and prevent abnormal transactions, minimizing losses caused by fraud.

[0066] In this embodiment, the fraud detection module consists of multiple sub-modules, mainly including a risk assessment module, a fraud behavior recognition module, a fraud detection result generation module, and a risk adjustment module. These sub-modules work together to ensure a comprehensive assessment of each transaction and take corresponding protection measures according to the risk level.

[0067] Generally, the workflow of the fraud detection module obtains the verification result from the transaction verification module. The transaction verification module has completed the decryption and legality verification of payment data to ensure that the transaction complies with basic rules. The fraud detection module further analyzes the verification result through the risk assessment module to identify potential fraud risks. Specifically, the system comprehensively evaluates factors such as the historical data, amount, transaction frequency, and transaction parties of the transaction to determine in real time whether there are abnormal behaviors in the transaction.

[0068] As an option, the risk assessment module can combine multiple data sources, such as historical transaction records, user behavior data, device information, etc., to evaluate the risk of the current transaction. By comparing normal and abnormal transaction patterns, the system can detect and mark possible fraud behaviors in real time. This process relies on powerful data analysis capabilities and pattern recognition algorithms to ensure the rapid and accurate detection of abnormal transactions.

[0069] Specifically, the risk assessment module quantitatively analyzes the risk of the transaction through the following formula: ; Among them, is the Risk Score, which is used to quantify the risk level of a transaction; is the Transaction Amount, that is, the amount of this transaction; is the TransactionFrequency, which refers to the number of transactions within a certain period of time; is the Sender Info, including the identity, account, behavioral characteristics, etc. of the payer; is the Receiver Info, including the identity, account, behavioral characteristics, etc. of the receiver; is the Device Info, which refers to the device - related parameters used in this transaction, including device ID, device location, device fingerprint, etc.; is the Other Factors, which refers to other associated factors that affect the risk score, such as IP address, geographical location, timestamp, network environment, etc.

[0070] In some embodiments, the fraud detection result generation module may also consider other factors, such as the current security level of the system, changes in the user's historical behavior, geographical location, etc., to further improve the accuracy of detection. Through multi - dimensional and multi - level analysis, the fraud detection module can efficiently identify and prevent fraud transactions.

[0071] The risk adjustment module adjusts the defense strategy according to the fraud detection result. When the system determines that a certain transaction is a high - risk or fraud transaction, the risk adjustment module will automatically trigger a response strategy. Possible response measures include, but are not limited to: increasing the identity verification requirements, temporarily freezing the account, restricting the payment amount, requiring more transaction vouchers, etc. These measures can effectively reduce the risk of the system being attacked by fraud and ensure the security of the payment process.

[0072] In some embodiments, the risk adjustment module may automatically increase the security verification requirements or suggest that the user conduct further identity confirmation to reduce the occurrence of fraud. In addition, the system can also feedback the results of fraud detection to relevant personnel or payment platforms through an automatic reporting function for further review and processing.

[0073] Through the design of the above fraud detection module, the present invention can effectively identify potential fraud behaviors in real time during the payment process and dynamically adjust the defense strategy according to the detection results. The system comprehensively evaluates the risks of transactions, identifies abnormal behavior patterns, and analyzes historical data to ensure that every transaction undergoes strict scrutiny. Ultimately, through the operation of the fraud detection module, fraud behaviors can be effectively prevented, risks reduced, and the security of payments guaranteed.

[0074] The implementation of this module not only enhances the defense capabilities of the payment system but also improves the system's adaptability to different types of fraud attacks, ensuring the efficient and secure processing of all transactions during the payment process.

[0075] A payment confirmation module, used to decide whether to complete a payment transaction according to the fraud detection results and transaction verification results; The main task of the payment confirmation module is to finally confirm and authorize all transactions screened by the fraud detection module, ensure the legality of the transactions, and provide feedback to the payer, payee, and the system. The payment confirmation module improves the security of transactions through a multiple verification mechanism, avoiding financial losses caused by fraud.

[0076] In this embodiment, the payment confirmation module consists of multiple sub-modules, mainly including a payment request receiving module, a payment verification module, a payment authorization module, and a payment feedback module. These modules work together to ensure that every transaction undergoes strict review and verification before confirmation, thus effectively preventing false payments and account theft.

[0077] Generally, the payment confirmation module first receives payment requests from the transaction system, including relevant data such as the payment amount, payer, payee, and transaction device information. These information will be preliminarily sorted and verified in the receiving module to ensure the integrity and validity of the payment request data. Then, the payment verification module will further verify the request, combining the output results of the aforementioned fraud detection module to determine whether the current transaction meets the payment conditions.

[0078] As an option, in some implementation methods, the payment confirmation module may need to be linked with an external identity authentication system (such as SMS verification, dynamic passwords, or fingerprint recognition, etc.) to enhance the security of transactions. The payment verification module further verifies the identity information of the payer by docking with the external authentication system to ensure that the payment request is initiated by a legitimate user.

[0079] Specifically, the payment verification module deeply analyzes the transaction information and calculates a payment verification score by combining multiple factors, such as the payment amount, transaction history, and the user's device information, etc., and decides whether to allow the transaction to continue according to the score. The operation of the verification module depends on the following formula: ; wherein, is the payment verification score, which is used to quantify the verification result of the transaction; is the payment amount (Amount), that is, the amount of the transaction; is the transaction frequency (Frequency), which refers to the number of transactions of the payer within a specific time; is the user's transaction history, including the historical transaction data of the payer, which is used to analyze their behavior patterns; is the device information (Device Info), including information such as the type of device used in the transaction and the device ID; is the identity information (ldentity Info), including the authentication information of the payer, such as SMS verification codes, fingerprint information, etc.

[0080] In a possible implementation, the payment verification score will be compared with a preset security threshold. If the verification score exceeds the threshold, the payment verification module will allow the transaction to continue; if the score is low, an additional verification mechanism will be triggered, or the transaction will be directly rejected. At this time, the payment verification module further authorizes the transaction through the payment authorization module.

[0081] In some embodiments, the payment authorization module may involve more complex authorization mechanisms. For example, in the case of high-value payments or bulk transactions, secondary confirmation or multi-factor authentication may be required to ensure the legality and security of the payment request. The system can perform secondary verification by calling the API interface of an external system, or require the payer to enter a specific dynamic password, etc.

[0082] Specifically, the payment authorization module will finally decide whether to authorize the transaction based on the feedback of the payment verification module and real-time risk control evaluation. In this case, the decision-making logic of the system can be described by the following formula: ; wherein, is the payment authorization decision (Payment Authorization Decision), which is the result of whether the transaction is authorized obtained through comprehensive analysis; is the payment verification score; is the risk score, which represents the risk assessment value of the transaction; is the transaction status, which represents the current status of the transaction, such as whether it is marked as high-risk, whether fraud detection has been completed, etc.

[0083] As an option, the payment confirmation module can also consider factors such as the security status of the system and the feedback from external verification agencies to further improve the accuracy and security of payment authorization. Through a multi-level and multi-factor verification mechanism, the security of each payment transaction is ensured.

[0084] In another embodiment, the payment feedback module provides timely feedback to the user based on the payment authorization result. If the transaction passes the verification and is successfully authorized, the user will receive a payment success notification; if the transaction fails the verification, the reason for rejecting the transaction will be provided to the payer, and the user will be prompted to re-verify the identity information or take other remedial measures.

[0085] Specifically, the payment feedback module not only feeds back the payment result to the user, but also feeds back the verification and authorization results to the system for subsequent risk assessment and adjustment by the system. These feedback messages play an important role in optimizing the entire payment process and risk control mechanism.

[0086] Through the design of the above payment confirmation module, the present invention can significantly improve the security of the payment system, ensuring that each transaction undergoes strict verification and authorization. Through a multi-verification mechanism and dynamic authorization control, the system can identify potential risks in real time and prevent the occurrence of fraudulent transactions. The implementation of this module not only enhances the security of the payment process, but also optimizes the user experience, ensuring that legitimate users can complete payments smoothly while minimizing losses caused by fraud.

[0087] By combining an external verification system and multi-dimensional analysis, the payment confirmation module ensures that every link of the transaction can be effectively monitored and controlled. Ultimately, through multi-verification, risk assessment, and real-time feedback, the payment confirmation module provides strong support for the security protection of the entire payment system.

[0088] Please refer to the appendix Figure 6 , the present invention also provides an offline payment anti-fraud method based on dynamic encryption technology, including the following steps: S1. Generate a dynamic payment key corresponding to the current transaction based on a high-dimensional chaotic system through a dynamic key generation module; S2. Perform non-linear topological encryption on the payment data through a payment data encryption module, and perform secondary encryption on the encrypted data in combination with the dynamic payment key; S3. Decrypt and verify the legality of the encrypted payment data through a transaction verification module to generate a transaction verification result; S4. Analyze the transaction verification result through a fraud detection module to identify whether there is fraud, generate a fraud detection result, and adjust the defense strategy; S5. Determine whether to execute the payment based on the transaction verification result and the fraud detection result through the payment confirmation module to complete the payment transaction or reject the execution.

[0089] For S1, at the start of a payment transaction, a dynamic payment key corresponding to the current transaction is generated by the dynamic key generation module based on a high-dimensional chaotic system.

[0090] Generally, a high-dimensional chaotic system has high randomness and unpredictability, which can ensure the uniqueness and security of the generated dynamic key in different transaction scenarios.

[0091] As an option, the generation of this key can be dynamically adjusted depending on factors such as the transaction timestamp, device characteristic parameters, and transaction user identity identifier, thereby enhancing the security and anti-attack ability of the key.

[0092] For S2, after the dynamic payment key is generated, the payment data enters the payment data encryption module for encryption processing.

[0093] Specifically, this module encrypts the payment data using a non-linear topological encryption method and performs secondary encryption in combination with the dynamic payment key to increase the complexity and security of the data.

[0094] In some embodiments, encryption techniques such as dynamic hash chains or block ciphers can be used in the encryption process to ensure that even if an attacker intercepts part of the data, the complete payment information cannot be restored.

[0095] In addition, this encryption process can be combined with a multi-layer random perturbation mechanism to further improve the irreversibility and anti-eavesdropping ability of the data.

[0096] For S3, the encrypted payment data will be decrypted and its legality verified by the transaction verification module to ensure the integrity and authenticity of the transaction data.

[0097] Generally, this verification process uses a reverse key calculation method, decrypts using the dynamic key, and checks whether the data is within the valid time range.

[0098] As an option, this module can also combine factors such as the user's historical transaction behavior and device authentication information to further improve the accuracy of legality determination.

[0099] In some embodiments, this verification process can use zero-knowledge proof (ZKP) or homomorphic encryption methods to ensure the integrity of the transaction data without exposing sensitive information.

[0100] For S4, after the transaction verification is completed, the fraud detection module analyzes the transaction verification result and identifies whether there is fraud.

[0101] Specifically, this module calculates the risk score of this transaction through a machine learning model, an anomaly detection algorithm, or a rule-based risk assessment system.

[0102] As an option, the fraud detection module can combine parameters such as the geographical location of the payer, device usage patterns, and transaction frequency to dynamically adjust the defense strategy in real time and improve the detection accuracy.

[0103] In some possible implementation manners, this module can combine a fraud detection model based on federated learning to achieve distributed intelligent detection and improve the adaptability of the system.

[0104] For S5, in the payment confirmation stage, the payment confirmation module determines whether to execute the payment according to the transaction verification result and the fraud detection result.

[0105] Generally, if the transaction is legal and the risk score is within the security threshold, the payment will be executed and the transaction will be completed; otherwise, the payment request will be rejected or the user will be required to perform additional identity verification.

[0106] As an option, the payment confirmation module can combine methods such as biometric verification (such as face recognition, fingerprint recognition) or two-factor authentication (such as SMS verification code, dynamic password) to improve the security of payment confirmation.

[0107] In some embodiments, this module can dynamically adjust the payment confirmation strategy according to parameters such as historical transaction records and user credit ratings, so as to improve the payment experience while ensuring transaction security.

[0108] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An offline payment fraud prevention system based on dynamic encryption technology, characterized in that, Comprising: A dynamic key generation module for generating a dynamic payment key in real time according to a high-dimensional chaotic system, generating a unique and non-repeating dynamic payment key for each transaction; A payment data encryption module for performing non-linear topological encryption on payment data and encrypting the encrypted data in combination with the dynamic payment key provided by the dynamic key generation module; A payment data encryption module for decrypting, verifying the encrypted payment data, and determining whether it is a legal transaction, generating a transaction verification result; A fraud detection module for detecting whether there is a fraud risk based on the transaction verification result, generating a fraud detection result, and adjusting the defense strategy according to the fraud detection result; A fraud detection module for deciding whether to complete the payment transaction according to the fraud detection result and the transaction verification result.

2. The offline payment anti-fraud system based on dynamic encryption technology according to claim 1, wherein The dynamic payment key is only valid in the current transaction, and no preset or long-term stored static payment key is required during the generation process, thereby improving the randomness of the key and the security of the payment transaction.

3. The offline payment anti-fraud system based on dynamic encryption technology according to claim 1, characterized in that, The high-dimensional chaotic system consists of multiple iterative equations, and the iterative equation is: ； Among them, is the state variable of the high-dimensional chaotic system at the -th iteration; is the state variable of the system at the -th iteration; is the control parameter of the chaotic system, which is a preset real constant; represents the discrete time step.

4. The offline payment fraud prevention system based on dynamic encryption technology according to claim 1, characterized in that, The payment data encryption module includes: A data preprocessing module for formatting and normalizing payment data; A non-linear topological encryption module for performing non-linear topological encryption on payment data; A dynamic key encryption module for performing secondary encryption on the encrypted data in combination with the dynamic payment key.

5. The offline payment anti-fraud system based on dynamic encryption technology according to claim 4, wherein The steps for performing non-linear topological encryption on payment data are: Performing block processing on payment data, dividing the payment data into multiple data blocks; Performing non-linear transformation on each data block, mapping the data block using a chaotic function; After each data block undergoes topological transformation, merging them; Encrypting the merged data block, and further encrypting it using the dynamic payment key.

6. The offline payment anti-fraud system based on dynamic encryption technology according to claim 1, characterized in that The steps for performing secondary encryption on the encrypted data in combination with the dynamic payment key are: Obtaining the generated dynamic payment key; Performing exclusive OR operation on the encrypted data using the dynamic payment key; Performing further encryption processing on the exclusive OR operation result to ensure the non-readability of the data; Outputting the finally encrypted payment data.

7. The offline payment anti-fraud system based on dynamic encryption technology according to claim 1, characterized in that, The transaction verification module includes: A data decryption module for decrypting the encrypted payment data; A legality verification module for verifying whether the decrypted payment data conforms to the predetermined transaction rules; A transaction verification result generation module for generating a legal transaction verification result and determining whether the transaction is valid.

8. The offline payment anti-fraud system based on dynamic encryption technology according to claim 1, characterized in that, The fraud detection module includes: A risk assessment module for assessing the transaction risk according to the transaction verification result; A fraud behavior identification module for detecting whether there is an abnormal transaction pattern; A fraud detection result generation module for generating a fraud detection result according to the outputs of the risk assessment module and the fraud behavior identification module; A risk adjustment module for adjusting the defense strategy according to the fraud detection result.

9. The offline payment fraud prevention system based on dynamic encryption technology according to claim 1, characterized in that, The payment confirmation module includes: A fraud detection result judgment module for judging whether there is a risk in the transaction according to the fraud detection result; A transaction verification result judgment module for judging whether the transaction is legal according to the transaction verification result; A payment execution module for performing the payment operation when the transaction is legal and there is no fraud risk.

10. The offline payment anti-fraud method based on dynamic encryption technology is applied to the offline payment anti-fraud system based on dynamic encryption technology as described in any one of claims 1-9, and is characterized in that, Including the following steps: The dynamic key generation module generates a dynamic payment key corresponding to the current transaction based on a high-dimensional chaotic system; The payment data encryption module performs non-linear topological encryption on the payment data and performs secondary encryption on the encrypted data in combination with the dynamic payment key; The transaction verification module decrypts and verifies the legality of the encrypted payment data to generate a transaction verification result; The fraud detection module analyzes the transaction verification result, identifies whether there is fraud, generates a fraud detection result and adjusts the defense strategy; The payment confirmation module determines whether to execute the payment according to the transaction verification result and the fraud detection result, and completes the payment transaction or refuses to execute.

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