Wireless payment system of intelligent consumption machine and transaction protection method thereof

Abstract

The invention provides a wireless payment system of an intelligent consumption machine and a transaction protection method thereof, and relates to the technical field of transaction protection, and the method comprises the steps: delimiting set verification according to initial transaction data, and obtaining the privacy sensitivity in a transaction data block when a transaction user carries out a transaction; determining a signature ciphertext information group of transaction data when the transaction user initiates a transaction request according to the security constraint, and submitting the signature ciphertext information group to a file synchronization contract when the consumption machine performs a transaction to obtain a transaction ciphertext data set when the consumption machine performs the transaction; according to the transaction consensus node and the privacy sensitivity, determining a security identifier ciphertext when transaction security verification is performed on the transaction data, and determining homomorphic privacy loss when the consumption machine performs the transaction; and according to the transaction ciphertext data set and the homomorphic privacy loss, performing dynamic protection on transaction data of the transaction user when the consumption machine performs transaction. The method can dynamically adapt to different transaction scenes and privacy requirements, so as to improve the privacy protection adaptation capability of transaction data in a consumption machine.

Description

Technical Field

[0001] The present application relates to the technical field of transaction protection, and more specifically, to a wireless payment system of an intelligent consumer machine and a transaction protection method thereof. Background Art

[0002] Transaction protection refers to the use of technical means and strategies to ensure the privacy, integrity, authenticity and security of transaction data during the transaction process, and to prevent unauthorized access, tampering or leakage of transaction information during transmission, storage and processing. The goal of transaction protection is to ensure that user sensitive information (such as personal identity, account data, transaction amount, etc.) is not stolen or tampered with by external attackers during the transaction process, while ensuring the legality and transparency of the transaction. In order to achieve effective transaction protection, multi-level security measures are usually adopted. Sensitive information is converted into an unreadable form through encryption algorithms to ensure that the data cannot be decrypted even if it is intercepted; authentication and authorization mechanisms to ensure that only legally authorized users and nodes can participate in transactions; data integrity verification to verify whether the data has been tampered with during transmission; and privacy protection technology to reduce the risk of leakage and protect personal privacy information involved in transactions.

[0003] Existing transaction protection methods for smart consumer machines usually rely on multiple encryption technologies, authentication mechanisms, and privacy protection measures to ensure transaction security and user privacy. First, the consumer machine will use end-to-end encryption to protect transaction data during the transaction process to ensure that the data will not be tampered with or leaked during transmission. Common encryption technologies include symmetric encryption and asymmetric encryption, among which asymmetric encryption (such as RSA, ECDSA) is usually used for digital signatures and identity authentication. Secondly, the integrity and legitimacy of transaction data are usually verified by digital signatures and hash algorithms to ensure that the data has not been tampered with during the transaction transmission process. Digital signatures use private keys to sign transaction information, and the verifier can use public keys to verify the authenticity of the data. However, existing transaction protection methods for smart consumer machines mainly rely on static encryption and authentication mechanisms. Although they can ensure the security of transaction data transmission, they usually lack dynamic assessment and targeted protection of transaction data privacy sensitivity. The protection of transaction data privacy is too static and fails to make fine-grained real-time adjustments for different types of data and privacy risks, which makes data with high privacy risks face the risk of privacy leakage during the transaction process, resulting in privacy protection measures that cannot be accurate and flexible, and cannot dynamically adapt to different transaction scenarios and privacy needs. Therefore, how to dynamically adapt to different transaction scenarios and privacy needs to improve the privacy protection adaptability of transaction data in consumer machines is a problem faced by the industry. Summary of the invention

[0004] The present application provides a wireless payment system for an intelligent consumer machine and a transaction protection method thereof, which can dynamically adapt to different transaction scenarios and privacy requirements to improve the privacy protection adaptability of transaction data in the consumer machine.

[0005] In a first aspect, the present application provides a transaction protection method for an intelligent consumer machine, the transaction protection method comprising the following steps:

[0006] Establish data communication of the wireless payment system in the consumer machine and obtain the initial transaction data of the transaction user when the consumer machine conducts the transaction;

[0007] Verify the set of initial transaction data to obtain the privacy sensitivity of the transaction data block when the transaction user conducts the transaction;

[0008] Obtain the security constraints when the transaction data in the consumer machine is exchanged, determine the signature ciphertext information group of the transaction data when the transaction user initiates a transaction request according to the security constraints, submit the signature ciphertext information group to the file synchronization contract when the consumer machine performs the transaction, and obtain the transaction ciphertext data set when the consumer machine performs the transaction;

[0009] Determine a transaction consensus node on a transaction data block, determine a security identification ciphertext for transaction data security verification according to the transaction consensus node and the privacy sensitivity, perform homomorphic verification on the security identification ciphertext, and obtain a homomorphic privacy loss when a consumer machine conducts a transaction;

[0010] The transaction data of the transaction user is dynamically protected when the consumer machine conducts transactions based on the transaction ciphertext data set and the homomorphic privacy loss.

[0011] In this embodiment, the initial transaction data refers to a set of basic information about the transaction received by the consumer terminal from the user terminal when the transaction is initiated.

[0012] In this embodiment, according to the initial transaction data set verification, the privacy sensitivity in the transaction data block when the transaction user conducts the transaction is obtained, which specifically includes:

[0013] Selecting a privacy-related numerical feature in the initial transaction data;

[0014] Determine the transaction log ciphertext in the transaction data block when the transaction user conducts the transaction;

[0015] The privacy numerical features are classified according to the transaction log ciphertext to obtain the privacy sensitivity in the transaction data block.

[0016] In this embodiment, the signature ciphertext information group of the transaction data when the transaction user initiates a transaction request according to the security constraint specifically includes:

[0017] Determining the degree of verification privacy when the user node initiates a transaction request according to the security constraints;

[0018] Obtain the privacy protection level of transaction data when the transaction user initiates a transaction request;

[0019] Determining the ciphertext data when the user initiates a transaction request according to the privacy protection level;

[0020] A signature ciphertext information group of transaction data when a transaction user initiates a transaction request is determined according to the verification privacy degree and the ciphertext data.

[0021] In this embodiment, the signed ciphertext information group is submitted to the file synchronization contract when the consumer machine performs a transaction, and the transaction ciphertext data set obtained when the consumer machine performs a transaction specifically includes:

[0022] Get the file synchronization contract when the consumer machine conducts transactions;

[0023] Determining the privacy balance constraint when the consumer machine conducts transactions according to the file synchronization contract;

[0024] The signed ciphertext information group is homomorphically verified through the privacy balance constraint to obtain a transaction ciphertext data set when the consumer machine conducts a transaction.

[0025] In this embodiment, determining the transaction consensus node on the transaction data block specifically includes:

[0026] Determine the transaction data block when the consumer machine conducts a transaction;

[0027] determining a transaction privacy feature of the transaction data according to the transaction data block;

[0028] A transaction consensus node on a transaction data block is determined based on the transaction privacy feature.

[0029] In this embodiment, the security identification ciphertext for transaction data to be processed for transaction security verification according to the transaction consensus node and the privacy sensitivity specifically includes:

[0030] Generate encrypted signature information of transaction data according to the transaction consensus node;

[0031] Determine the trustworthiness measure during transaction security verification by using the privacy sensitivity;

[0032] Determine the encryption verification score when performing transaction security verification on transaction data;

[0033] The security identification ciphertext when performing transaction security verification on the transaction data is determined according to the encrypted signature information, the trustworthiness measure and the encrypted verification score.

[0034] In this embodiment, the security identification ciphertext is homomorphically verified to obtain the homomorphic privacy loss when the consumer machine conducts a transaction, which specifically includes:

[0035] Determining the homomorphic association amount when the aircraft is trading according to the security identification ciphertext;

[0036] Identify public verification information when an aircraft is traded;

[0037] The homomorphic privacy loss when the consumer machine conducts a transaction is determined by the homomorphic association amount and the public verification information.

[0038] In this embodiment, the signature ciphertext information group refers to an information set consisting of encrypted transaction data and corresponding digital signatures.

[0039] In a second aspect, the present application provides a wireless payment system for an intelligent consumer machine, which is used to execute a transaction protection method for an intelligent consumer machine, and the wireless payment system includes:

[0040] The transaction data acquisition module is used to establish data communication of the wireless payment system in the consumer machine and obtain the initial transaction data of the transaction user when the consumer machine conducts a transaction;

[0041] A data set verification module, used to define a set verification based on the initial transaction data to obtain the privacy sensitivity in the transaction data block when the transaction user conducts the transaction;

[0042] The ciphertext information submission module is used to obtain the security constraints when the transaction data in the consumer machine is exchanged, determine the signature ciphertext information group of the transaction data when the transaction user initiates the transaction request according to the security constraints, submit the signature ciphertext information group to the file synchronization contract when the consumer machine performs the transaction, and obtain the transaction ciphertext data set when the consumer machine performs the transaction;

[0043] A transaction security verification module is used to determine the transaction consensus node on the transaction data block, determine the security identification ciphertext when the transaction data is subjected to transaction security verification according to the transaction consensus node and the privacy sensitivity, perform homomorphic verification on the security identification ciphertext, and obtain the homomorphic privacy loss when the consumer machine conducts the transaction;

[0044] The transaction dynamic protection module is used to dynamically protect the transaction data of the transaction user when the consumer machine conducts transactions based on the transaction ciphertext data set and the homomorphic privacy loss.

[0045] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0046] Establish data communication of the wireless payment system in the consumer machine, obtain the initial transaction data of the transaction user when the consumer machine conducts the transaction; define a set verification based on the initial transaction data to obtain the privacy sensitivity in the transaction data block when the transaction user conducts the transaction; obtain the security constraints when the transaction data in the consumer machine is exchanged, determine the signature ciphertext information group of the transaction data when the transaction user initiates a transaction request based on the security constraints, submit the signature ciphertext information group to the file synchronization contract when the consumer machine conducts the transaction, and obtain the transaction ciphertext data set when the consumer machine conducts the transaction; determine the transaction consensus node on the transaction data block, determine the security identification ciphertext when the transaction data is subjected to transaction security verification based on the transaction consensus node and the privacy sensitivity, perform homomorphic verification on the security identification ciphertext, and obtain the homomorphic privacy loss when the consumer machine conducts the transaction; dynamically protect the transaction data of the transaction user when the consumer machine conducts the transaction based on the transaction ciphertext data set and the homomorphic privacy loss.

[0047] It can be seen that in this application, privacy data leakage can be effectively prevented; among them, by establishing stable and secure wireless data communication, the initial transaction data of the transaction user can be obtained in real time to ensure that the basic information of the transaction is fully recorded; by evaluating the privacy sensitivity of the transaction data, the highly sensitive information in the data can be dynamically identified, so as to provide more stringent privacy protection measures for sensitive data during the transaction process, and ensure the security of high privacy data in the entire transaction process; by formulating clear security constraints and using signed ciphertext information groups, the integrity and confidentiality of the transaction data can be ensured during the exchange process, and the effective synchronization and consistency of the transaction data can be guaranteed by the file synchronization contract, further enhancing the security and legitimacy of the transaction data; through the transaction consensus node and homomorphic verification technology of the blockchain, the intelligent verification of the privacy of the transaction data is realized, ensuring that the legitimacy of the privacy data is effectively evaluated without decryption, and obtaining the measure of privacy loss, thereby providing a basis for the dynamic protection mechanism and optimizing the privacy risk control; through the dynamic protection mechanism, according to the real-time privacy loss evaluation and the ciphertext data set, the protection strategy of the transaction data can be flexibly adjusted, and the protection measures can be intelligently enhanced or weakened according to the changes in privacy risks, ensuring that the privacy data is always in the best protection state during the transaction process, improving the transaction security and reducing the risk of privacy leakage.

[0048] In summary, the technical solution adopted in this application can dynamically adapt to different transaction scenarios and privacy requirements to improve the privacy protection adaptability of transaction data in consumer machines. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0050] Figure 1 It is a flow chart of the transaction protection method of the smart consumer machine provided by the present application;

[0051] Figure 2 It is a schematic diagram of the process of determining the signature ciphertext information group provided by this application;

[0052] Figure 3 It is a schematic diagram of the process of determining the security identification ciphertext provided by this application;

[0053] Figure 4 It is a module structure diagram of the wireless payment system of the smart consumer machine provided in this application. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0055] The embodiment of the present application provides a wireless payment system of an intelligent consumer machine and a transaction protection method thereof, the core of which is to establish data communication of the wireless payment system in the consumer machine, obtain the initial transaction data of the transaction user when the consumer machine conducts a transaction; delimit a set of verifications based on the initial transaction data to obtain the privacy sensitivity in the transaction data block when the transaction user conducts a transaction; obtain the security constraints when the transaction data in the consumer machine is exchanged, determine the signature ciphertext information group of the transaction data when the transaction user initiates a transaction request based on the security constraints, submit the signature ciphertext information group to the file synchronization contract when the consumer machine conducts a transaction, and obtain the transaction ciphertext data set when the consumer machine conducts a transaction; determine the transaction consensus node on the transaction data block, determine the security identification ciphertext when the transaction data is subjected to transaction security verification based on the transaction consensus node and the privacy sensitivity, perform homomorphic verification on the security identification ciphertext, and obtain the homomorphic privacy loss when the consumer machine conducts a transaction; dynamically protect the transaction data of the transaction user when the consumer machine conducts a transaction based on the transaction ciphertext data set and the homomorphic privacy loss. The above scheme can dynamically adapt to different transaction scenarios and privacy requirements to improve the privacy protection adaptability of transaction data in the consumer machine.

[0056] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown, this figure is an exemplary flow chart of the transaction protection method of the smart consumer machine shown in this embodiment of the present application, and the transaction protection method includes the following steps:

[0057] In step S1, data communication of the wireless payment system in the consumer machine is established to obtain the initial transaction data of the transaction user when the consumer machine conducts a transaction.

[0058] In specific implementation, when establishing the data communication of the wireless payment system in the consumer machine, it is first necessary to ensure that the consumer machine can receive the initial transaction data of the transaction user. The implementation of this process usually relies on wireless communication protocols, such as NFC (near field communication), Bluetooth or Wi-Fi. Specifically, when a user initiates a payment request through a mobile device (such as a smart phone, bank card or smart watch), the consumer machine establishes a connection with the user's device through the corresponding wireless communication module. Taking NFC as an example, the user only needs to bring the device close to the consumer machine, and the NFC card reader of the consumer machine will be activated and receive the payment information in the user's device. This information includes preliminary transaction data such as the user's identity (such as a credit card number or account ID), payment amount, transaction type, device information and timestamp. To ensure the security and integrity of the data, encryption technology is usually used during the transmission process, such as TLS or SSL protocol to encrypt the data to prevent the data from being tampered with or stolen during the transmission process. At the same time, the consumer machine will also perform preliminary verification on the received transaction data to ensure the validity of the data and the legitimacy of the source, which will not be repeated here.

[0059] It should be noted that, in this application, initial transaction data refers to a set of basic information about the transaction received by the consumer machine from the user end when the transaction is initiated.

[0060] In step S2, the initial transaction data is demarcated and verified to obtain the privacy sensitivity in the transaction data block when the transaction user conducts the transaction.

[0061] In this embodiment, according to the initial transaction data set verification, the privacy sensitivity in the transaction data block when the transaction user conducts the transaction can be obtained by the following steps:

[0062] Selecting a privacy-related numerical feature in the initial transaction data;

[0063] Determine the transaction log ciphertext in the transaction data block when the transaction user conducts the transaction;

[0064] The privacy numerical features are classified according to the transaction log ciphertext to obtain the privacy sensitivity in the transaction data block.

[0065] In the specific implementation, first of all, it is necessary to identify which data belongs to private information. These data usually include sensitive data such as user identity information, payment amount, transaction account, bank card number, etc. These private numerical features can be extracted from the initial transaction data through data mining and feature recognition technology. For example: user identity information (such as the user's bank account, credit card number or mobile phone number); payment amount (the amount usually contains high privacy, especially when paying large amounts); payment method (such as bank card, digital wallet, credit card, etc.); transaction timestamp (although not directly private data, it may reveal user behavior patterns together with other data). The system identifies and extracts these numerical features through preset rules or machine learning models. Then, in order to protect the private numerical features, the information in the transaction data needs to be encrypted. At this time, the transaction log ciphertext is the encrypted transaction data set. The transaction log usually records all the details of the transaction, including user identity, payment amount, transaction time and other information. During the encryption process, these logs are encrypted using encryption algorithms (such as AES, RSA, etc.) to ensure the security of data during storage and transmission. Specifically, the system selects an appropriate encryption algorithm to encrypt the data in the transaction log according to the sensitivity of the privacy numerical feature; the encrypted data is called the transaction log ciphertext, which ensures that the data content cannot be interpreted even if the data is illegally accessed. Finally, when the transaction log ciphertext is generated, the system will classify and divide the data according to the nature and sensitivity of the privacy numerical feature. Generally, privacy sensitivity is divided into several levels: high-sensitivity data: such as user identity, bank card number, account balance, etc.; medium-sensitivity data: such as transaction amount, payment method, etc.; low-sensitivity data: such as transaction time, device ID, etc. The system analyzes the encrypted transaction log ciphertext and combines the classification rules of the privacy numerical feature to classify each data field in the transaction data block into different privacy sensitivity levels. This process may use statistical analysis, machine learning and other technologies to dynamically adjust according to the potential risks and usage scenarios of the data.

[0066] It should be noted that in this application, privacy numerical features refer to information features that may expose the user's personal privacy in transaction data, such as identity identification code, account information, payment amount, etc.; transaction log ciphertext refers to the ciphertext data generated by processing transaction log data through an encryption algorithm, which is used to protect privacy information during the transaction process; privacy sensitivity refers to the degree of protection required for privacy information contained in transaction data. According to the sensitivity of the data, it is divided into different levels, usually including high sensitivity, medium sensitivity and low sensitivity.

[0067] In step S3, the security constraints for data exchange of transaction data in the consumer machine are obtained, and the signature ciphertext information group of the transaction data when the transaction user initiates a transaction request is determined according to the security constraints. The signature ciphertext information group is submitted to the file synchronization contract when the consumer machine conducts the transaction, and the transaction ciphertext data set when the consumer machine conducts the transaction is obtained.

[0068] In specific implementation, the security constraints for obtaining transaction data in the consumer machine for data exchange can be implemented in the following way, namely: first, before exchanging data, the consumer machine must ensure that the communication with other systems or devices is secure. To this end, the transaction data will be protected by encryption protocols (such as TLS / SSL) during the exchange process. The TLS protocol can encrypt the transmission channel to ensure that the data is not eavesdropped or tampered with during the transmission process, and at the same time verify the identities of both parties in the communication to prevent middleman attacks. Secondly, for sensitive information in the transaction data, the consumer opportunity will encrypt the data according to the preset security policy. For example, highly sensitive data such as transaction amount and user identity information are encrypted using symmetric encryption algorithms (such as AES) to ensure that even if the data is intercepted, it cannot be read by unauthorized parties. In addition, the identity authentication mechanism is also a key part of the security constraint. The consumer opportunity verifies the identity of the initiator of the transaction request through digital signatures or two-factor authentication to ensure that the requester is a legitimate user. For example, when paying, the user may need to authenticate through a PIN code or biometrics (such as fingerprints, facial recognition). Finally, the consumer machine will also limit the authority of data exchange according to the access control policy to ensure that only authorized users and systems can access or modify transaction data.

[0069] It should be noted that, in this application, security constraints refer to the rules set during data exchange, storage and processing to ensure the confidentiality, integrity and availability of information.

[0070] Preferably, in this embodiment, the signature ciphertext information group of the transaction data when the transaction user initiates a transaction request is determined according to the security constraint, referring to Figure 2 The figure is a schematic diagram of a process for determining a signature ciphertext information group in some embodiments of the present application. In this embodiment, determining a signature ciphertext information group can be implemented by the following steps:

[0071] In step S31, the verification privacy when the user node initiates a transaction request is determined according to the security constraint;

[0072] In step S32, the privacy protection level of the transaction data when the transaction user initiates the transaction request is obtained;

[0073] In step S33, the ciphertext data when the user initiates the transaction request is determined according to the privacy protection level;

[0074] In step S34, a signature ciphertext information group of the transaction data when the transaction user initiates a transaction request is determined according to the verification privacy level and the ciphertext data.

[0075] In the specific implementation, first, the privacy data involved when the transaction user initiates a transaction request is evaluated according to the pre-set security constraints. For example, the user's identity information may be evaluated as high privacy, while the transaction time and device information may be low privacy. Through security constraints, the system determines which information requires stronger verification protection. Then, the system further evaluates the privacy protection level of the data based on the initial transaction data provided by the transaction user and the determined verification privacy. For example, highly sensitive data such as user identity and bank card number may be assigned a "high privacy protection level", while transaction time, device information, etc. may belong to a "low privacy protection level". When determining the privacy protection level, a privacy protection model (such as differential privacy) may be used to ensure the privacy of data at different processing stages. Then, the system will encrypt the transaction data. For data with a high privacy protection level, a stronger encryption algorithm (such as RSA, AES, etc.) is used for encryption and ciphertext data is generated. For example, for identity information and bank card numbers, strong encryption algorithms (such as RSA or AES-256) are used to generate ciphertext; for low-privacy data, lightweight encryption technology or hashing algorithms may be used for processing. The goal of encryption is to ensure that even if the transaction data is intercepted, unauthorized persons cannot read the data content. Finally, after completing the encryption and privacy protection of the transaction data, the next step is to digitally sign the encrypted data and generate a signed ciphertext information group. The process includes: the system uses the encrypted data and the preset private key to digitally sign to ensure the integrity, source and non-repudiation of the transaction data; the signature information and the encrypted ciphertext data are combined to form a signed ciphertext information group, which will be sent to the transaction system or target service along with the transaction request. According to the previous verification privacy and privacy protection level, different levels of privacy data will use different signature algorithms and encryption strengths. For example, the signature of high-privacy data may use a stronger encryption algorithm and a more complex signature mechanism.

[0076] It should be noted that in this application, verification privacy refers to the determination of the required privacy protection and verification strength based on the privacy sensitivity of the data during the transaction process. A higher verification privacy requires more stringent encryption and verification measures; the privacy protection level refers to the strength and method of data protection set according to the sensitivity of the data and legal and compliance requirements; ciphertext data refers to the result of encrypting the original transaction data through an encryption algorithm, and only the authorized party holding the corresponding decryption key can access the original data; the signature ciphertext information group refers to the information set consisting of the encrypted transaction data and the corresponding digital signature, which is used to ensure that the data is not tampered with during transmission and to prove its legitimacy and integrity.

[0077] In this embodiment, the signed ciphertext information group is submitted to the file synchronization contract when the consumer machine performs a transaction, and the transaction ciphertext data set when the consumer machine performs a transaction can be obtained by the following steps:

[0078] Get the file synchronization contract when the consumer machine conducts transactions;

[0079] Determining the privacy balance constraint when the consumer machine conducts transactions according to the file synchronization contract;

[0080] The signed ciphertext information group is homomorphically verified through the privacy balance constraint to obtain a transaction ciphertext data set when the consumer machine conducts a transaction.

[0081] In the specific implementation, first, during the transaction process, there needs to be a clear set of protocols or contracts between the consumer machine and other systems to ensure the synchronization and consistency of data exchange. The file synchronization contract is defined by the transaction system or payment platform, which stipulates how to handle the exchange, encryption, synchronization and related privacy protection requirements of transaction data. The specific operation is: when the transaction request reaches the consumer machine, the consumer machine automatically obtains the file synchronization contract related to the current transaction according to the system settings or transaction protocol. This contract usually includes how to handle privacy data, encryption method of transaction data, transmission specifications and data synchronization rules. The file synchronization contract is the "contract" between the two parties in the data exchange, which ensures the security and consistency of transaction data during the transmission process. Then, based on the obtained file synchronization contract, the consumer opportunity will determine the privacy protection requirements of the transaction data and the related privacy balance constraints according to the terms therein. Privacy balance constraints mainly refer to how to allow transaction data to be effectively exchanged between systems while ensuring data privacy. Specifically, the file synchronization contract will define a privacy balance mechanism, which sets privacy constraints based on the balance between the privacy protection requirements of transaction data and the operability of transaction operations. For example, for highly sensitive data, strict regulations on encryption strength, access rights, and verification measures may be required; consumers will implement specific data protection strategies based on these privacy balance constraints to ensure that unnecessary private information is not leaked, while ensuring the smooth progress of transaction operations. Finally, homomorphic encryption allows calculations on encrypted data to maintain its privacy. For example, the consumer can verify whether the data is consistent with the original data and whether it has not been tampered with without decrypting the signed ciphertext; when performing homomorphic verification, the consumer will apply privacy balance constraints to ensure that the verification process meets privacy protection requirements. If the privacy protection level is higher, a stronger homomorphic encryption scheme may be used to ensure that sensitive information is not leaked during the processing of transaction data; after the homomorphic verification is completed, the consumer will obtain a verified transaction ciphertext data set, which contains verified and encrypted data.

[0082] It should be noted that in this application, the file synchronization contract refers to a set of protocols or rules that define how to synchronize and process the privacy, encryption and decryption requirements of transaction data during the data exchange process to ensure the correct and secure exchange of transaction data; the privacy balance constraint refers to a strategy that ensures the privacy of data while not excessively affecting the system performance or the smooth progress of transactions during the transaction data exchange process; transaction ciphertext data set.

[0083] In step S4, the transaction consensus node on the transaction data block is determined, and the security identification ciphertext for transaction security verification of the transaction data is determined according to the transaction consensus node and the privacy sensitivity. The security identification ciphertext is homomorphically verified to obtain the homomorphic privacy loss when the consumer machine conducts the transaction.

[0084] In this embodiment, determining the transaction consensus node on the transaction data block can be achieved by using the following steps:

[0085] Determine the transaction data block when the consumer machine conducts a transaction;

[0086] determining a transaction privacy feature of the transaction data according to the transaction data block;

[0087] A transaction consensus node on a transaction data block is determined based on the transaction privacy feature.

[0088] In the specific implementation, first, during the transaction process, the transaction data generated by the consumer machine will be organized into a transaction data block. This block is a collection of data, which contains all the key information of the transaction, including user identity, payment amount, payment time, transaction status, transaction device information, etc. The transaction data block is the basic unit of data in the entire transaction process, including: when the user initiates a transaction request and completes the payment, the consumer machine will collect transaction information from the transaction data source (such as payment terminal, bank system, etc.) and organize it into a data block. This information includes but is not limited to transaction ID, user account, amount, payment method, timestamp, etc.; the transaction data block needs to be encrypted and signed to ensure the confidentiality and integrity of its data. The encrypted transaction data block can be safely transmitted and stored between the consumer machine and other systems. Then, after determining the transaction data block, the consumer machine needs to analyze and extract the privacy information in the data block to determine the transaction privacy characteristics of the data. These privacy characteristics refer to the parts of the transaction data that may expose the user's privacy, such as: user identity information (such as account number, credit card number, etc.);

[0089] Payment amount (large payments may expose the user's financial situation); transaction timestamp (transaction time can reflect user behavior patterns); payment device information (device model, IP address, etc. may leak user device characteristics). Finally, if the transaction data involves highly sensitive privacy features (such as user identity, transaction amount, etc.), the system may select a consensus node with higher authority to process this data; if the privacy features are relatively simple and the privacy requirements of the transaction data are low, nodes with lower authority can participate in the consensus. The selection of transaction consensus nodes can be dynamically adjusted through an evaluation algorithm based on privacy features. For example, in large-scale transactions, transaction privacy features may involve the consensus of multiple nodes to ensure the security and accuracy of the data. The consensus node is responsible for verifying the legitimacy of the transaction, completing encryption verification, and ensuring that the data has not been tampered with.

[0090] It should be noted that in this application, a transaction data block refers to a data unit that packages and encrypts transaction-related information (such as transaction amount, user identity, timestamp, etc.) during a transaction. It is often used in blockchain and encrypted transaction systems to represent a complete transaction data; transaction privacy features refer to features or attributes in transaction data that may expose user privacy, such as identity information, transaction amount, payment method, etc.; transaction consensus nodes refer to key points in blockchain or decentralized networks that are responsible for verifying transaction data.

[0091] Preferably, in this embodiment, the security identification ciphertext for transaction data security verification is determined according to the transaction consensus node and the privacy sensitivity, referring to Figure 3 The figure is a schematic diagram of a process for determining a security identification ciphertext in some embodiments of the present application. In this embodiment, determining the security identification ciphertext can be implemented by the following steps:

[0092] In step S41, encrypted signature information of the transaction data is generated according to the transaction consensus node;

[0093] In step S42, a trust measure for transaction security verification is determined by using the privacy sensitivity;

[0094] In step S43, the encryption verification score for transaction data during transaction security verification is determined;

[0095] In step S44, a security identification ciphertext for transaction data to be used for transaction security verification is determined according to the encrypted signature information, the trustworthiness metric and the encrypted verification score.

[0096] In the specific implementation, first, the consensus node will use its private key to digitally sign the transaction data. The signature is an encryption operation on the content of the transaction data (including transaction amount, transaction time, user information, etc.) to ensure that the data has not been tampered with and comes from a legitimate node. The integrity and authenticity of the transaction data can be verified through digital signatures. After signing, the generated encrypted signature information will be sent to the downstream system along with the transaction data for subsequent verification and verification. For example, the signature is generated using the RSA or ECDSA algorithm, in which the data is hashed and encrypted, and the signature is attached to the transaction data block. The signature information ensures the immutability and legal source of the transaction data; then, based on the privacy characteristics of the transaction data (such as user identity information, transaction amount, etc.), its privacy sensitivity is evaluated. Highly sensitive data (such as identity information and account information) will receive a higher privacy sensitivity assessment. Based on the privacy sensitivity, the system will assign a corresponding trust metric to the transaction data. For example, the trust metric can be implemented through a scoring system. For example, if the transaction involves highly sensitive information, the trust metric may be 0.9; if it is ordinary transaction data, the trust metric may be 0.5; then, the verification score of the transaction data is obtained by weighted calculation of factors such as encryption signature, privacy sensitivity, transaction amount, and transaction time. For example, sensitive data (such as account number and identity information) may be given a higher weight to increase the verification score. The purpose of the verification score is to ensure that the security verification process not only relies on the encryption signature, but also includes comprehensive considerations of privacy protection and data integrity. The higher the score, the higher the security and privacy protection requirements of the transaction data. Finally, the system will encrypt the encryption signature, trust metric, and encryption verification score through an encryption algorithm to generate the final security identification ciphertext. The ciphertext will serve as a security label for the transaction data and as a basis for verification during the transaction verification process. The security identification ciphertext usually includes the encrypted signature of the transaction data, an indication of privacy sensitivity, verification points and other information to ensure that both the authenticity and privacy requirements of the data can be handled simultaneously during transaction verification.

[0097] It should be noted that in this application, the encrypted signature information refers to the digital signature generated by an encryption algorithm (such as RSA, ECDSA), which proves the legitimacy and non-tampering of the transaction data. The encrypted signature relies on the private key of the signer, and only the node with the corresponding public key can verify the validity of the signature; the trust metric refers to the standard used to measure the authenticity and security of transaction data during the transaction data security verification process. The trust metric is determined based on privacy sensitivity and security requirements, reflecting the confidentiality and verification requirements of the data; the encrypted verification score refers to the verification value calculated by comprehensively evaluating factors such as the encrypted signature, privacy sensitivity and trust metric of the transaction data. This score is used to evaluate the security and verification requirements of transaction data; the security identification ciphertext represents the security identification of the transaction data during the transaction verification process, and the ciphertext is used to verify the integrity, legitimacy and privacy protection requirements of the data.

[0098] In this embodiment, homomorphic verification is performed on the security identification ciphertext to obtain the homomorphic privacy loss when the consumer machine conducts a transaction. The following steps can be used to achieve this:

[0099] Determining the homomorphic association amount when the aircraft is trading according to the security identification ciphertext;

[0100] Identify public verification information when an aircraft is traded;

[0101] The homomorphic privacy loss when the consumer machine conducts a transaction is determined by the homomorphic association amount and the public verification information.

[0102] In the specific implementation, first, from the security identification ciphertext, the consumer will extract the encrypted transaction data signature information, privacy features, verification points and other contents. These encrypted information contain the key features of the transaction data and do not directly expose any private data. The homomorphic correlation is a measure or identification of the encrypted part of the transaction data related to the private information. Under the homomorphic encryption framework, the consumer will determine which encrypted information is closely related to the private data by operating on the encrypted data. This information constitutes the "homomorphic correlation"; then, the public verification information usually includes the basic information of the transaction, such as the transaction timestamp, payment method, merchant information, etc., which does not involve any user privacy. The consumer obtains this public information by accessing the transaction data block and blockchain system. In the homomorphic encryption process, the public key is often used for verification. The consumer verifies the encrypted data by using the public key related to the transaction data to ensure the legitimacy of the source of the data. Finally, the consumer will compare the homomorphic correlation and the public verification information to evaluate whether there is a risk of privacy information leakage in the homomorphic encryption process. For example, if an encrypted field is overused during the verification process, it may cause the risk of privacy leakage, thereby increasing privacy loss. Based on homomorphic encryption technology, the consumer machine can calculate different degrees of privacy loss. For example, the leakage of private information may be manifested as the exposure of the correlation of encrypted data during the processing process, or the leakage of part of the original data through multiple verifications; through calculation, the consumer machine obtains a measure of privacy loss, namely homomorphic privacy loss.

[0103] It should be noted that in this application, homomorphic correlation refers to a measure used to measure the correlation between encrypted data under the framework of homomorphic encryption. It represents the relationship between encrypted data and private information, and can evaluate the impact of private information without decrypting the data; public verification information refers to information that can be publicly obtained and used during the transaction verification process. This information usually does not involve sensitive data, but can be used to verify the compliance, legality or other non-privacy attributes of the transaction; homomorphic privacy loss refers to the degree of private data leakage caused by verification operations during homomorphic encryption. It measures the risk and loss of private information exposure during the encryption process.

[0104] In step S5, the transaction data of the transaction user when the consumer machine conducts a transaction is dynamically protected according to the transaction ciphertext data set and the homomorphic privacy loss.

[0105] In the specific implementation, the consumer machine first needs to parse and process the transaction ciphertext data set, which consists of encrypted signature information, transaction log ciphertext, privacy protection level, etc. Each transaction data set contains sensitive information of the transaction user (such as account information, transaction amount, etc.), and this data is protected by homomorphic encryption. The consumer machine identifies the type and sensitivity of private information by analyzing each encrypted element in the ciphertext data set. For example, some transaction data may involve high privacy features (such as user identity, payment method, etc.), while others may be relatively ordinary. Next, the consumer machine evaluates the privacy protection requirements of the transaction data based on the calculation results of homomorphic privacy loss. If the privacy loss is high, it means that the risk of privacy leakage during the transaction process is high, and the system needs to take more stringent protection measures; on the contrary, if the privacy loss is low, the protection measures can be moderately relaxed. For example, during the transaction process, if the homomorphic privacy loss of a data field is high, the consumer machine may need to increase the encryption strength of the field, or choose not to disclose the data to the public. Then, based on the analysis of the transaction ciphertext data set and the evaluation of privacy loss, the consumer machine will dynamically adjust the privacy protection strategy, that is: based on the analysis of the transaction ciphertext data set and the evaluation of privacy loss, the consumer machine will dynamically adjust the privacy protection strategy; for data with high privacy risks, the consumer machine can limit the transmission and disclosure of data, and only minimize data sharing when necessary; in order to further protect sensitive information, the consumer machine may use privacy masking technology, such as data desensitization or data anonymization, to convert sensitive data into an unrecognizable form to avoid information leakage. Finally, during the transaction, the consumer opportunity will monitor the privacy protection effect of the transaction data in real time. If a potential privacy leakage risk is detected during the transaction execution (such as abnormal changes in encrypted data), the consumer opportunity will dynamically adjust the protection measures. For example, by implementing a real-time risk assessment system, the consumer machine can timely adjust the encryption strength or take other protection measures according to the current changes in privacy loss to ensure that the transaction data is always highly protected throughout the transaction process. I will not go into details here.

[0106] It can be seen that in this application, privacy data leakage can be effectively prevented; among them, by establishing stable and secure wireless data communication, the initial transaction data of the transaction user can be obtained in real time to ensure that the basic information of the transaction is fully recorded; by evaluating the privacy sensitivity of the transaction data, the highly sensitive information in the data can be dynamically identified, so as to provide more stringent privacy protection measures for sensitive data during the transaction process, and ensure the security of high privacy data in the entire transaction process; by formulating clear security constraints and using signed ciphertext information groups, the integrity and confidentiality of the transaction data can be ensured during the exchange process, and the effective synchronization and consistency of the transaction data can be guaranteed by the file synchronization contract, further enhancing the security and legitimacy of the transaction data; through the transaction consensus node and homomorphic verification technology of the blockchain, the intelligent verification of the privacy of the transaction data is realized, ensuring that the legitimacy of the privacy data is effectively evaluated without decryption, and obtaining the measure of privacy loss, thereby providing a basis for the dynamic protection mechanism and optimizing the privacy risk control; through the dynamic protection mechanism, according to the real-time privacy loss evaluation and the ciphertext data set, the protection strategy of the transaction data can be flexibly adjusted, and the protection measures can be intelligently enhanced or weakened according to the changes in privacy risks, ensuring that the privacy data is always in the best protection state during the transaction process, improving the transaction security and reducing the risk of privacy leakage.

[0107] In summary, the technical solution adopted in this application can dynamically adapt to different transaction scenarios and privacy requirements to improve the privacy protection adaptability of transaction data in consumer machines.

[0108] This application provides a wireless payment system for an intelligent consumer machine, referring to Figure 4 As shown, this figure is a schematic diagram of a wireless payment system of a smart consumer machine according to this embodiment of the present application, and the wireless payment system includes:

[0109] The transaction data acquisition module 100 is used to establish data communication of the wireless payment system in the consumer machine and obtain the initial transaction data of the transaction user when the consumer machine conducts a transaction;

[0110] A data set verification module 200, for performing set verification based on the initial transaction data to obtain the privacy sensitivity in the transaction data block when the transaction user conducts the transaction;

[0111] The ciphertext information submission module 300 is used to obtain the security constraints when the transaction data in the consumer machine is exchanged, determine the signature ciphertext information group of the transaction data when the transaction user initiates the transaction request according to the security constraints, submit the signature ciphertext information group to the file synchronization contract when the consumer machine performs the transaction, and obtain the transaction ciphertext data set when the consumer machine performs the transaction;

[0112] The transaction security verification module 400 is used to determine the transaction consensus node on the transaction data block, determine the security identification ciphertext when the transaction data is subjected to transaction security verification according to the transaction consensus node and the privacy sensitivity, perform homomorphic verification on the security identification ciphertext, and obtain the homomorphic privacy loss when the consumer machine conducts the transaction;

[0113] The transaction dynamic protection module 500 is used to dynamically protect the transaction data of the transaction user when the consumer machine conducts transactions based on the transaction ciphertext data set and the homomorphic privacy loss.

[0114] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0115] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0116] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A transaction protection method for an intelligent consumer machine, characterized in that: The transaction protection method comprises the following steps: Establish data communication of the wireless payment system in the consumer machine and obtain the initial transaction data of the transaction user when the consumer machine conducts the transaction; Verify the set of initial transaction data to obtain the privacy sensitivity of the transaction data block when the transaction user conducts the transaction; Obtain the security constraints when the transaction data in the consumer machine is exchanged, determine the signature ciphertext information group of the transaction data when the transaction user initiates a transaction request according to the security constraints, submit the signature ciphertext information group to the file synchronization contract when the consumer machine performs the transaction, and obtain the transaction ciphertext data set when the consumer machine performs the transaction; Determine a transaction consensus node on a transaction data block, determine a security identification ciphertext for transaction data security verification according to the transaction consensus node and the privacy sensitivity, perform homomorphic verification on the security identification ciphertext, and obtain a homomorphic privacy loss when a consumer machine conducts a transaction; The transaction data of the transaction user is dynamically protected when the consumer machine conducts transactions based on the transaction ciphertext data set and the homomorphic privacy loss.

2. A transaction protection method for an intelligent consumer machine as claimed in claim 1, characterized in that: The initial transaction data refers to a set of basic information about the transaction received by the consumer terminal from the user terminal when the transaction is initiated.

3. A transaction protection method for an intelligent consumer machine as claimed in claim 1, characterized in that: According to the initial transaction data set verification, the privacy sensitivity in the transaction data block when the transaction user conducts the transaction specifically includes: Selecting a privacy-related numerical feature in the initial transaction data; Determine the transaction log ciphertext in the transaction data block when the transaction user conducts the transaction; The privacy numerical features are classified according to the transaction log ciphertext to obtain the privacy sensitivity in the transaction data block.

4. A transaction protection method for an intelligent consumer machine as claimed in claim 1, characterized in that: Determining the signature ciphertext information group of transaction data when a transaction user initiates a transaction request according to the security constraint specifically includes: Determining the degree of verification privacy when the user node initiates a transaction request according to the security constraints; Obtain the privacy protection level of transaction data when the transaction user initiates a transaction request; Determining the ciphertext data when the user initiates a transaction request according to the privacy protection level; A signature ciphertext information group of transaction data when a transaction user initiates a transaction request is determined according to the verification privacy degree and the ciphertext data.

5. A transaction protection method for an intelligent consumer machine as claimed in claim 1, characterized in that: Submit the signed ciphertext information group to the file synchronization contract when the consumer machine conducts a transaction, and obtain the transaction ciphertext data set when the consumer machine conducts a transaction, which specifically includes: Get the file synchronization contract when the consumer machine conducts transactions; Determining the privacy balance constraint when the consumer machine conducts transactions according to the file synchronization contract; The signed ciphertext information group is homomorphically verified through the privacy balance constraint to obtain a transaction ciphertext data set when the consumer machine conducts a transaction.

6. A transaction protection method for an intelligent consumer machine as claimed in claim 1, characterized in that: The transaction consensus nodes on the transaction data block include: Determine the transaction data block when the consumer machine conducts a transaction; determining a transaction privacy feature of the transaction data according to the transaction data block; A transaction consensus node on a transaction data block is determined based on the transaction privacy feature.

7. A transaction protection method for an intelligent consumer machine as claimed in claim 1, characterized in that: The security identification ciphertext for performing transaction security verification on transaction data determined according to the transaction consensus node and the privacy sensitivity specifically includes: Generate encrypted signature information of transaction data according to the transaction consensus node; Determine the trustworthiness measure during transaction security verification by using the privacy sensitivity; Determine the encryption verification score when performing transaction security verification on transaction data; The security identification ciphertext when performing transaction security verification on the transaction data is determined according to the encrypted signature information, the trustworthiness measure and the encrypted verification score.

8. A transaction protection method for an intelligent consumer machine as claimed in claim 1, characterized in that: The security identification ciphertext is homomorphically verified to obtain the homomorphic privacy loss when the consumer machine conducts a transaction, which specifically includes: Determining the homomorphic association amount when the aircraft is trading according to the security identification ciphertext; Identify public verification information when an aircraft is traded; The homomorphic privacy loss when the consumer machine conducts a transaction is determined by the homomorphic association amount and the public verification information.

9. A transaction protection method for an intelligent consumer machine as claimed in claim 1, characterized in that: The signature ciphertext information group refers to an information set consisting of encrypted transaction data and the corresponding digital signature.

10. A wireless payment system for an intelligent consumer machine, used to execute a transaction protection method for an intelligent consumer machine as claimed in any one of claims 1 to 9, characterized in that: The wireless payment system comprises: The transaction data acquisition module is used to establish data communication of the wireless payment system in the consumer machine and obtain the initial transaction data of the transaction user when the consumer machine conducts a transaction; A data set verification module, used to define a set verification based on the initial transaction data to obtain the privacy sensitivity in the transaction data block when the transaction user conducts the transaction; The ciphertext information submission module is used to obtain the security constraints when the transaction data in the consumer machine is exchanged, determine the signature ciphertext information group of the transaction data when the transaction user initiates the transaction request according to the security constraints, submit the signature ciphertext information group to the file synchronization contract when the consumer machine performs the transaction, and obtain the transaction ciphertext data set when the consumer machine performs the transaction; A transaction security verification module is used to determine the transaction consensus node on the transaction data block, determine the security identification ciphertext when the transaction data is subjected to transaction security verification according to the transaction consensus node and the privacy sensitivity, perform homomorphic verification on the security identification ciphertext, and obtain the homomorphic privacy loss when the consumer machine conducts the transaction; The transaction dynamic protection module is used to dynamically protect the transaction data of the transaction user when the consumer machine conducts transactions based on the transaction ciphertext data set and the homomorphic privacy loss.

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