Sandbox data isolation and anonymization method and device, equipment and medium

Abstract

The invention relates to the field of data security technology and financial science and technology, and discloses a sandbox data isolation and anonymization method, device and equipment and a storage medium, the method comprises the following steps: constructing a data isolation strategy according to acquired financial service data, constructing a sandbox environment according to the data isolation strategy, and storing the sandbox environment in the sandbox environment; performing security classification on the financial service data in the sandbox environment to obtain sensitive data and non-sensitive data, performing anonymization on the sensitive data to obtain anonymous data, performing data fuzzification on the non-sensitive data to obtain desensitized data, and storing the desensitized data in the sandbox environment; and monitoring the data access of the anonymous data and the desensitized data in the sandbox environment in real time to obtain a security log record of the sandbox environment. According to the method, the data security can be effectively improved, and the user privacy can be well protected.

Description

Technical Field

[0001] The present invention relates to the fields of data security technology and financial technology, and in particular to a sandbox data isolation and anonymization method, device, electronic device and computer-readable storage medium. Background Art

[0002] Data isolation and anonymization of financial business systems are important solutions in the field of data security technology. They are mainly used to ensure that the sandbox system is completely isolated from the production environment, and to randomize sensitive fields in the data to prevent real user data from leaking during testing. The open banking sandbox system is a test platform used to simulate a real environment for third-party developers and partners to conduct integration testing. It is crucial to protect the security and privacy of user data in this environment.

[0003] Currently, the industry mainly creates isolated container environments to isolate different applications or developers from each other when running on the same physical server, but there are generally some defects and shortcomings: First, although the sandbox system can simulate some real environments, it cannot completely restore all complexities and risks, so it cannot cover all potential problems and vulnerabilities. Secondly, despite the isolation measures, the risk of data leakage or cross-access still exists in some cases. In addition, the anonymization technology of traditional solutions cannot provide comprehensive data protection capabilities, and there are many problems such as destroying the availability and testability of data.

[0004] The current existing technologies have problems with low data security and poor user privacy protection. Summary of the invention

[0005] The present invention provides a sandbox data isolation and anonymization method, device, electronic device and computer-readable storage medium, the main purpose of which is to solve the problems of low data security and poor user privacy protection function.

[0006] In a first aspect, to achieve the above-mentioned purpose, the present invention provides a sandbox data isolation and anonymization method, comprising:

[0007] Build data isolation strategies based on acquired financial business data;

[0008] Building a sandbox environment according to the data isolation strategy;

[0009] Security classification of the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data;

[0010] Anonymizing the sensitive data to obtain anonymous data;

[0011] Obfuscating the non-sensitive data to obtain desensitized data;

[0012] Data access to the anonymous data and the desensitized data is monitored in real time in the sandbox environment to obtain security log records of the sandbox environment.

[0013] In a second aspect, the present invention also provides a sandbox data isolation and anonymization device, the device comprising:

[0014] A strategy acquisition module is used to build a data isolation strategy based on the acquired financial business data;

[0015] An environment building module, used to build a sandbox environment according to the data isolation strategy;

[0016] A data classification module, used to perform security classification on the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data;

[0017] A data anonymization module, used to anonymize the sensitive data to obtain anonymous data;

[0018] A data obfuscation module, used to obfuscate the non-sensitive data to obtain desensitized data;

[0019] The real-time monitoring module is used to monitor the data access to the anonymous data and the desensitized data in real time in the sandbox environment to obtain the security log record of the sandbox environment.

[0020] In a third aspect, the present invention further provides an electronic device, the electronic device comprising:

[0021] at least one processor; and,

[0022] a memory communicatively connected to the at least one processor; wherein,

[0023] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the sandbox data isolation and anonymization method described above.

[0024] In a fourth aspect, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is executed by a processor in an electronic device to implement the above-mentioned sandbox data isolation and anonymization method.

[0025] The present invention constructs a data isolation strategy according to the acquired financial business data, builds a sandbox environment according to the data isolation strategy, performs security classification on the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data, distinguishes sensitive data from non-sensitive data, reduces the risk of information leakage when the data is used, anonymizes the sensitive data to obtain anonymous data, and randomly generates an initial vector to enhance the security of encryption, ensuring that even the anonymous data generated in different encryption processes for the same sensitive data will be different, thereby preventing attackers from performing analysis through anonymous data, performs data obfuscation on the non-sensitive data to obtain desensitized data, retains the statistical characteristics of the data, and reduces the risk of possible leakage of personal identity, performs real-time monitoring on data access to the anonymous data and the desensitized data in the sandbox environment, obtains security log records of the sandbox environment, provides a reliable data basis for subsequent security audits and analyses, effectively improves data security, and better protects user privacy. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0027] Figure 1 is a schematic diagram of an application environment of a sandbox data isolation and anonymization method in one embodiment of the present invention;

[0028] Figure 2 A schematic diagram of a process flow of a sandbox data isolation and anonymization method provided by an embodiment of the present invention;

[0029] Figure 3 A schematic diagram of a module of a sandbox data isolation and anonymization device provided by an embodiment of the present invention;

[0030] Figure 4 A schematic diagram of the structure of an electronic device for implementing a sandbox data isolation and anonymization method provided by an embodiment of the present invention;

[0031] Figure 5 It is another structural schematic diagram of an electronic device for implementing a sandbox data isolation and anonymization method provided by an embodiment of the present invention.

[0032] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, and to fully understand and implement how the present disclosure applies technical means to solve technical problems and achieve the corresponding technical effects, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0035] The embodiments of the present application provide a sandbox data isolation and anonymization method, and the execution subject of the sandbox data isolation and anonymization method includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the device provided by the embodiments of the present application. In other words, the sandbox data isolation and anonymization method can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0036] The sandbox data isolation and anonymization method of the embodiment of the present invention can be applied to Figure 1In the application environment. Among them, the client communicates with the server through the network. The server can construct a data isolation strategy through the financial business data obtained by the client, build a sandbox environment according to the data isolation strategy, perform security classification on the financial business data in the sandbox environment, obtain sensitive data and non-sensitive data, distinguish sensitive data from non-sensitive data, so that the risk of information leakage is reduced when the data is used, anonymize the sensitive data to obtain anonymous data, and obfuscate the non-sensitive data to obtain desensitized data. In the sandbox environment, data access to the anonymous data and the desensitized data is monitored in real time to obtain the security log record of the sandbox environment, and the final security log record is fed back to the client. Among them, the client can be but is not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server can be implemented with an independent server or a server cluster consisting of multiple servers. The present invention is described in detail below through specific embodiments.

[0037] Reference Figure 2 FIG. 1 is a flow chart of a sandbox data isolation and anonymization method provided in an embodiment of the present invention. In this embodiment, the sandbox data isolation and anonymization method includes:

[0038] S1. Build a data isolation strategy based on the acquired financial business data.

[0039] In the embodiment of the present invention, the financial business data is isolated according to the requirements of the financial business, and the data isolation strategy is determined, including: the granularity, level and boundary of data isolation. The financial business requirements, such as transaction data, user information and system logs, have different data sensitivities, and the granularity of isolation is also different; the data that the visitor can access can be determined based on the visitor's role, such as developer, application, etc., and different roles correspond to different isolation levels.

[0040] Data isolation is a key measure to ensure data security and compliance in financial business, especially when handling sensitive information and complying with regulatory requirements. In order to effectively implement data isolation strategy, it is necessary to clarify the granularity, hierarchy and boundaries of data isolation.

[0041] In detail, the data isolation strategy is constructed based on the acquired financial business data, including:

[0042] Extracting user level, application level and data classification information from the financial service data;

[0043] Matching the customer information in the financial service data to a preset customer service personnel according to the user level to obtain a user level isolation granularity;

[0044] Isolating the financial services in the financial service data according to the application level to obtain an application level isolation granularity;

[0045] Generating data classification granularity of the financial business data by using the data classification information;

[0046] Extracting employee data from the financial business data;

[0047] Generate data isolation levels and boundaries based on the access rights of the employee data;

[0048] A data isolation strategy is constructed using the user-level isolation granularity, the application-level isolation granularity, the data classification granularity, the hierarchy and the boundary.

[0049] Furthermore, financial companies provide a variety of financial services, including personal loans, investment management, and payment processing. When processing customer data, set the following data isolation granularity:

[0050] User-level isolation: Customer service representatives can only access loan application data related to the customers they are responsible for, and cannot access information of other customers. Investment advisors can only access the investment account information of customers; Application-level isolation: The data between the loan management system and the investment management system are completely isolated to ensure that the information between the two will not be accessed by each other, avoiding customer trust issues caused by data leakage; Data classification isolation: Data is divided into four categories: public data (such as interest rate information), internal data (such as company policies), sensitive data (such as customers' social security numbers), and highly sensitive data (such as bank card numbers). Highly sensitive data will be more strictly isolated and protected.

[0051] At the data isolation level, the following measures are taken: Role-based access control (RBAC) is implemented to ensure that employees in different roles can only access data related to their work. For example, the compliance department can access all types of data for auditing, but ordinary customer service representatives can only access some information.

[0052] The boundary of data isolation means that personal customer data (such as name, address, contact information) is completely separated from internal company data (such as employee information, company financial data). Customers' personal information should not be mixed with internal operational data.

[0053] Data isolation sets clear access permissions so that only employees with the appropriate permissions can access specific categories of data. For example, only compliance auditors can view sensitive data. There will also be data transfer boundaries: when data transfer is required, ensure that all transfers are encrypted and integrity checks are performed during the transfer process. For example, when loan application data is shared with a third-party credit reporting company, it is transmitted using a secure API and encrypted using HTTPS.

[0054] By extracting the user level, application level, and data classification information of financial business data, we can achieve accurate isolation of customer information and financial business. This isolation can not only match customer information to a specific user level based on the preset customer service personnel to ensure the personalization and efficiency of the service, but also effectively manage different financial businesses at the application level. Data classification information helps us refine data management and achieve more flexible classification granularity. In addition, considering the access rights of employee data in advance and building corresponding levels and boundaries can enhance data security and compliance and improve the efficiency and security of data management.

[0055] S2. Build a sandbox environment according to the data isolation strategy.

[0056] In an embodiment of the present invention, a secure testing and development environment is created to facilitate analysis, testing and application development of the financial business data without affecting the production environment.

[0057] In detail, the building of a sandbox environment according to the data isolation strategy includes:

[0058] Utilizing the user-level isolation granularity in the data isolation policy to configure an access environment for the customer service personnel;

[0059] Creating different sandbox containers according to the application level isolation granularity in the data isolation strategy;

[0060] Setting different access policies according to the data classification granularity in the data isolation policy;

[0061] The sandbox environment is built according to the access environment, the sandbox container and the access policy.

[0062] In detail, the access environment is classified according to the users and applications of the sandbox environment, and users are grouped, such as developers, testers, third-party applications, etc. Each group is assigned specific permissions, and different roles or applications can have different access rights. Configure specific permissions for each role, such as: create, read, update, and delete, and dynamically adjust the permissions of the role according to business needs to ensure that each role can only access data within its scope of responsibility. At the same time, set dynamic permission policies based on the attributes of the visitor, such as role, IP address, time, and device, and configure different permission levels based on attributes such as time, location, and device type. Formal application of the configured permission rules in the sandbox environment ensures that all access requests comply with the permission policy. And test the permissions of each role or application item by item to ensure that the permission allocation is accurate.

[0063] S3. Security classification is performed on the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data.

[0064] It is crucial to extract sensitive features from the financial business data, which may include personal information of customers, transaction records, etc. These sensitive features are used to identify sensitive data in the financial business data, and the parts of the standard business data that do not involve sensitive information are classified as non-sensitive data, thereby providing a more secure environment for subsequent data analysis and application.

[0065] In the embodiment of the present invention, the security classification of the financial service data in the sandbox environment to obtain sensitive data and non-sensitive data includes:

[0066] Calculating the average value of the financial business data;

[0067] Filling missing values ​​of the financial business data with the average value to obtain standard business data;

[0068] Extracting sensitive features of the standard business data;

[0069] Using the sensitive features to match the standard business data one by one to obtain sensitive data;

[0070] The remaining data in the standard business data except the sensitive data is regarded as non-sensitive data.

[0071] In detail, sensitive data includes: personal identity information: such as name, address, ID number, date of birth, etc.; financial information: such as bank account information, credit card number, transaction records, assets and liabilities, etc.; health information: if relevant, any data related to the customer's health status; trade secrets: such as internal company financial reports, business plans, etc.

[0072] Standard business data is formed by calculating the average value of financial business data and filling in missing values. This standardization process helps improve the integrity and consistency of data, making subsequent analysis more reliable. Extracting sensitive features and matching them can effectively identify and protect information involving personal privacy or commercial secrets, distinguish sensitive data from non-sensitive data, reduce the risk of information leakage when using data, and provide a clear perspective for subsequent business decisions and data analysis.

[0073] S4. Anonymize the sensitive data to obtain anonymous data.

[0074] Under the premise of ensuring the validity and availability of data, personal or sensitive information is protected from being leaked. At the same time, anonymization rules and methods are designed in combination with financial business needs, data types and privacy protection goals. Different strategies such as data masking and encryption are designed according to different sensitivities. Encryption algorithms are used to encrypt sensitive data that requires high protection to ensure that even if the data is leaked, the plaintext data cannot be directly obtained.

[0075] SM4 (National Secret Algorithm) is a symmetric encryption algorithm, mainly used to protect sensitive data. SM4 uses a 128-bit key to process data in 128-bit groups, that is, the length of each encrypted or decrypted data block is 16 bytes. It supports multiple encryption modes, such as Electronic Codebook Mode (ECB), Cipher Block Chaining Mode (CBC), Counter Mode (CTR), etc. The following are the steps to encrypt data using the SM4 algorithm.

[0076] In the embodiment of the present invention, the step of anonymizing the sensitive data to obtain anonymous data includes:

[0077] Get a randomly generated initial vector;

[0078] generating a symmetric key based on the sensitive data;

[0079] Determine whether the size of the sensitive data meets the preset SM4 block size;

[0080] If the size of the sensitive data does not conform to the preset SM4 block size, padding the sensitive data;

[0081] If the size of the sensitive data meets the preset SM4 block size, the sensitive data is sent to a preset SM4 encryptor using the initial vector and the symmetric key to obtain anonymous data.

[0082] In detail, the anonymous data is sent to a preset initialized SM4 decryptor using the same key and initialization vector to generate padded sensitive data. Since the sensitive data is padded during the encryption process, the padding needs to be removed after decryption to restore the original sensitive data. The padding removal usually uses the same padding scheme as that used for encryption.

[0083] The randomly generated initialization vector enhances the security of encryption, ensuring that even the same sensitive data will generate different anonymous data in different encryption processes, thereby preventing attackers from analyzing anonymous data. By generating a pair of symmetric keys, the access rights to the data can be effectively controlled to ensure that only users holding the keys can decrypt the data. The size of sensitive data is verified and necessary padding is performed to ensure that the data meets the block size requirements of the SM4 algorithm, enhancing the integrity and effectiveness of encryption. Not only does it protect sensitive information, it also improves the flexibility and security of the system's data processing, thereby reducing the risk of data leakage.

[0084] S5. Obfuscate the non-sensitive data to obtain desensitized data.

[0085] Data generalization is a common data obfuscation technology that mainly converts specific data into a broader category or range to achieve the purpose of protecting privacy. Generalizing the non-sensitive data can effectively protect the user's privacy, ensure data security, and extract useful information from it.

[0086] In the embodiment of the present invention, the step of performing data obfuscation on the non-sensitive data to obtain desensitized data includes:

[0087] Generate generalized rules based on non-sensitive data;

[0088] The non-sensitive data is converted according to the generalization rule to obtain desensitized data.

[0089] Specifically, generalization rules are formulated based on the data type and application scenario of the non-sensitive data. For example, age can be defined as age groups (such as "20-29 years old", "30-39 years old"); for geographic location, the specific address can be converted into the name of the city or province; for income, the specific income range can be replaced with an income group (such as "less than 5,000 yuan", "5,000-10,000 yuan").

[0090] Formulating generalization rules based on non-sensitive data can effectively convert specific information into broader categories, such as specifying age into age groups, simplifying addresses into city or province names, and breaking down income into intervals. These generalization rules generate desensitized data during the conversion process, which not only retains the statistical characteristics of the data but also reduces the risk of leaking personal identities. While meeting privacy protection and data security, it can still provide reliable information support for data analysis and decision-making.

[0091] S6. Perform real-time monitoring on data access to the anonymous data and the desensitized data in the sandbox environment to obtain security log records of the sandbox environment.

[0092] In the sandbox environment, all types of data operations are monitored in real time to ensure that any access to sensitive data is recorded and any abnormal operations or potential data leakage risks are detected in a timely manner. Key monitoring points: data reading and writing operations, data transmission, user identity authentication, and encryption and decryption operations of sensitive data.

[0093] In an embodiment of the present invention, real-time monitoring of data access to the anonymous data and the desensitized data in the sandbox environment to obtain a security log record of the sandbox environment includes:

[0094] Monitoring operation records on the anonymous data and the desensitized data;

[0095] Determining whether the operation record is a preset abnormal event;

[0096] If the operation record is not a preset abnormal event, continue to monitor the operation records of the anonymous data and the desensitized data;

[0097] If the operation record is a preset abnormal event, identifying the level of the abnormal event;

[0098] If the level of the abnormal event is a preset low level, an alarm is triggered and real-time monitoring continues;

[0099] If the level of the abnormal event is the preset medium level, the account of the abnormal event is automatically locked;

[0100] If the level of the abnormal event is a preset high level, immediately disconnecting the terminal connection of the abnormal event;

[0101] The normal events and the abnormal events are aggregated to obtain a security log record of the sandbox environment.

[0102] Recording and analyzing operations on anonymous and desensitized data not only monitors and responds to potential security threats in real time, but also takes corresponding countermeasures according to the level of abnormal events to ensure effective management of low, medium, and high-level threats. For example, triggering alarms for low-level events for continuous monitoring, automatically locking accounts for medium-level events, and immediately disconnecting terminal connections for high-level events can quickly reduce potential losses. At the same time, summarizing the log records of normal and abnormal events provides a reliable data foundation for subsequent security audits and analysis, helping organizations continuously optimize security strategies and improve protection capabilities.

[0103] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0104] like Figure 3 , which is a functional module diagram of a sandbox data isolation and anonymization device provided in one embodiment of the present invention.

[0105] In the embodiment of the present disclosure, a sandbox data isolation and anonymization device is provided, which corresponds one-to-one to the sandbox data isolation and anonymization method in the above embodiment. Figure 3 As shown, the sandbox data isolation and anonymization device 100 can be installed in an electronic device. According to the functions to be implemented, the sandbox data isolation and anonymization device 100 includes a policy acquisition module 101, an environment building module 102, a data classification module 103, a data anonymization module 104, a data fuzzy module 105 and a real-time monitoring module 106. The functional modules are described in detail as follows:

[0106] A strategy acquisition module 101, used to construct a data isolation strategy based on the acquired financial business data;

[0107] An environment building module 102, used to build a sandbox environment according to the data isolation strategy;

[0108] A data classification module 103, used to perform security classification on the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data;

[0109] A data anonymization module 104, used to anonymize the sensitive data to obtain anonymous data;

[0110] A data obfuscation module 105 is used to obfuscate the non-sensitive data to obtain desensitized data;

[0111] The real-time monitoring module 106 is used to monitor the data access to the anonymous data and the desensitized data in real time in the sandbox environment to obtain the security log record of the sandbox environment.

[0112] In one embodiment, when executing the construction of a data isolation policy based on the acquired financial service data, the policy acquisition module 101 is used to:

[0113] Extracting user level, application level and data classification information from the financial service data;

[0114] Matching the customer information in the financial service data to a preset customer service personnel according to the user level to obtain a user level isolation granularity;

[0115] Isolating the financial services in the financial service data according to the application level to obtain an application level isolation granularity;

[0116] Generating data classification granularity of the financial business data by using the data classification information;

[0117] Extracting employee data from the financial business data;

[0118] Generate data isolation levels and boundaries based on the access rights of the employee data;

[0119] A data isolation strategy is constructed using the user-level isolation granularity, the application-level isolation granularity, the data classification granularity, the hierarchy and the boundary.

[0120] In one embodiment, when executing the construction of the sandbox environment according to the data isolation strategy, the environment construction module 102 is used to:

[0121] Utilizing the user-level isolation granularity in the data isolation policy to configure an access environment for the customer service personnel;

[0122] Creating different sandbox containers according to the application level isolation granularity in the data isolation strategy;

[0123] Setting different access policies according to the data classification granularity in the data isolation policy;

[0124] The sandbox environment is built according to the access environment, the sandbox container and the access policy.

[0125] In one embodiment, when the data classification module 103 performs security classification on the financial service data in the sandbox environment to obtain sensitive data and non-sensitive data, it is used to:

[0126] Calculating the average value of the financial business data;

[0127] Filling missing values ​​of the financial business data with the average value to obtain standard business data;

[0128] Extracting sensitive features of the standard business data;

[0129] Using the sensitive features to match the standard business data one by one to obtain sensitive data;

[0130] The remaining data in the standard business data except the sensitive data is regarded as non-sensitive data.

[0131] In one embodiment, when the data anonymization module 104 performs anonymization on the sensitive data to obtain anonymous data, it is used to:

[0132] Get a randomly generated initial vector;

[0133] generating a symmetric key based on the sensitive data;

[0134] Determine whether the size of the sensitive data meets the preset SM4 block size;

[0135] If the size of the sensitive data does not conform to the preset SM4 block size, padding the sensitive data;

[0136] If the size of the sensitive data meets the preset SM4 block size, the sensitive data is sent to a preset SM4 encryptor using the initial vector and the symmetric key to obtain anonymous data.

[0137] In one embodiment, when the data obfuscation module 105 performs data obfuscation on the non-sensitive data to obtain desensitized data, it is used to:

[0138] Generate generalized rules based on non-sensitive data;

[0139] The non-sensitive data is converted according to the generalization rule to obtain desensitized data.

[0140] In one embodiment, when the real-time monitoring module 106 performs real-time monitoring on data access to the anonymous data and the desensitized data in the sandbox environment to obtain a security log record of the sandbox environment, it is used to:

[0141] Monitoring operation records on the anonymous data and the desensitized data;

[0142] Determining whether the operation record is a preset abnormal event;

[0143] If the operation record is not a preset abnormal event, continue to monitor the operation records of the anonymous data and the desensitized data;

[0144] If the operation record is a preset abnormal event, identifying the level of the abnormal event;

[0145] If the level of the abnormal event is a preset low level, an alarm is triggered and real-time monitoring continues;

[0146] If the level of the abnormal event is the preset medium level, the account of the abnormal event is automatically locked;

[0147] If the level of the abnormal event is a preset high level, immediately disconnecting the terminal connection of the abnormal event;

[0148] The normal events and the abnormal events are aggregated to obtain a security log record of the sandbox environment.

[0149] In the present invention, for sandbox data isolation and anonymization, first, a data isolation strategy is constructed according to the acquired financial business data, and a sandbox environment is built according to the data isolation strategy. Then, in the sandbox environment, the financial business data is securely classified to obtain sensitive data and non-sensitive data, and sensitive data is distinguished from non-sensitive data, so that the risk of information leakage is reduced when the data is used, and the sensitive data is anonymized to obtain anonymous data. The randomly generated initial vector enhances the security of encryption, ensuring that even the same sensitive data will be different in the anonymous data generated in different encryption processes, thereby preventing attackers from analyzing through anonymous data, and the non-sensitive data is obfuscated to obtain desensitized data, which not only retains the statistical characteristics of the data, but also reduces the risk of possible disclosure of personal identity. Finally, in the sandbox environment, data access to the anonymous data and the desensitized data is monitored in real time to obtain the security log record of the sandbox environment, which provides a reliable data basis for subsequent security audits and analyses, effectively improves data security and better protects user privacy. The specific definition of the sandbox data isolation and anonymization device can be found in the above definition of the sandbox data isolation and anonymization method, which will not be repeated here. Each module in the above-mentioned sandbox data isolation and anonymization device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0150] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, the functions or steps on the server side of the sandbox data isolation and anonymization method are implemented.

[0151] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Figure 5As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, the functions or steps on the client side of the sandbox data isolation and anonymization method are implemented.

[0152] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0153] Build data isolation strategies based on acquired financial business data;

[0154] Building a sandbox environment according to the data isolation strategy;

[0155] Security classification of the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data;

[0156] Anonymizing the sensitive data to obtain anonymous data;

[0157] Obfuscating the non-sensitive data to obtain desensitized data;

[0158] Data access to the anonymous data and the desensitized data is monitored in real time in the sandbox environment to obtain security log records of the sandbox environment.

[0159] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and apparatuses can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0160] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0161] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0162] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0163] In some implementations of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented.

[0164] The readable storage medium of the present invention stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can achieve:

[0165] Build data isolation strategies based on acquired financial business data;

[0166] Building a sandbox environment according to the data isolation strategy;

[0167] Security classification of the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data;

[0168] Anonymizing the sensitive data to obtain anonymous data;

[0169] Obfuscating the non-sensitive data to obtain desensitized data;

[0170] Data access to the anonymous data and the desensitized data is monitored in real time in the sandbox environment to obtain security log records of the sandbox environment.

[0171] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0172] The computer-readable storage medium may also store at least one computer executable program / instruction, which may be, for example, a computer-readable instruction. The computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The computer-readable storage medium may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device runs the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0173] In addition, the computer device may also include (but not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (eg, keyboard, mouse, speaker, etc.), etc.

[0174] The processor may communicate with external devices via an I / O bus via a wired or wireless network.

[0175] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0176] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0177] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0178] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0179] It should be noted that in the present disclosure, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article 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, article or device. In the absence of further restrictions, an element limited by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0180] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

[0181] It should be noted that if software tools or components other than those of our company appear in the embodiments of the present application, they are only used for illustrative purposes and do not represent actual use.

Claims

1. A sandbox data isolation and anonymization method, characterized in that: The method comprises: Build data isolation strategies based on acquired financial business data; Building a sandbox environment according to the data isolation strategy; Security classification of the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data; Anonymizing the sensitive data to obtain anonymous data; Obfuscating the non-sensitive data to obtain desensitized data; Data access to the anonymous data and the desensitized data is monitored in real time in the sandbox environment to obtain security log records of the sandbox environment.

2. The sandbox data isolation and anonymization method according to claim 1, characterized in that: The data isolation strategy is constructed based on the acquired financial business data, including: Extracting user level, application level and data classification information from the financial service data; Matching the customer information in the financial service data to a preset customer service personnel according to the user level to obtain a user level isolation granularity; Isolating the financial services in the financial service data according to the application level to obtain an application level isolation granularity; Generating data classification granularity of the financial business data using the data classification information; Extracting employee data from the financial business data; Generate data isolation levels and boundaries based on the access rights of the employee data; A data isolation strategy is constructed using the user-level isolation granularity, the application-level isolation granularity, the data classification granularity, the hierarchy and the boundary.

3. The sandbox data isolation and anonymization method according to claim 1, characterized in that: The step of building a sandbox environment according to the data isolation strategy includes: Using the user-level isolation granularity in the data isolation policy to configure an access environment for the customer service personnel; Creating different sandbox containers according to the application level isolation granularity in the data isolation strategy; Setting different access policies according to the data classification granularity in the data isolation policy; The sandbox environment is built according to the access environment, the sandbox container and the access policy.

4. The sandbox data isolation and anonymization method according to claim 1, characterized in that: The security classification of the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data includes: Calculating the average value of the financial business data; Filling missing values ​​of the financial business data with the average value to obtain standard business data; Extracting sensitive features of the standard business data; Using the sensitive features to match the standard business data one by one to obtain sensitive data; The remaining data in the standard business data except the sensitive data is regarded as non-sensitive data.

5. The sandbox data isolation and anonymization method according to claim 1, characterized in that: The step of anonymizing the sensitive data to obtain anonymous data includes: Get a randomly generated initial vector; generating a symmetric key based on the sensitive data; Determine whether the size of the sensitive data meets the preset SM4 block size; If the size of the sensitive data does not conform to the preset SM4 block size, padding the sensitive data; If the size of the sensitive data meets the preset SM4 block size, the sensitive data is sent to a preset SM4 encryptor using the initial vector and the symmetric key to obtain anonymous data.

6. The sandbox data isolation and anonymization method according to claim 1, characterized in that: The step of performing data obfuscation on the non-sensitive data to obtain desensitized data includes: Generate generalized rules based on non-sensitive data; The non-sensitive data is converted according to the generalization rule to obtain desensitized data.

7. The sandbox data isolation and anonymization method according to claim 1, characterized in that: The real-time monitoring of data access to the anonymous data and the desensitized data in the sandbox environment to obtain a security log record of the sandbox environment includes: Monitoring operation records on the anonymous data and the desensitized data; Determining whether the operation record is a preset abnormal event; If the operation record is not a preset abnormal event, continue to monitor the operation records of the anonymous data and the desensitized data; If the operation record is a preset abnormal event, identifying the level of the abnormal event; If the level of the abnormal event is a preset low level, an alarm is triggered and real-time monitoring continues; If the level of the abnormal event is the preset medium level, the account of the abnormal event is automatically locked; If the level of the abnormal event is a preset high level, immediately disconnecting the terminal connection of the abnormal event; The normal events and the abnormal events are aggregated to obtain a security log record of the sandbox environment.

8. A sandbox data isolation and anonymization device, characterized in that: The device comprises: A strategy acquisition module is used to build a data isolation strategy based on the acquired financial business data; An environment building module, used to build a sandbox environment according to the data isolation strategy; A data classification module, used to perform security classification on the financial business data in the sandbox environment to obtain sensitive data and non-sensitive data; A data anonymization module, used to anonymize the sensitive data to obtain anonymous data; A data obfuscation module, used to obfuscate the non-sensitive data to obtain desensitized data; The real-time monitoring module is used to monitor the data access to the anonymous data and the desensitized data in real time in the sandbox environment to obtain the security log record of the sandbox environment.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the sandbox data isolation and anonymization method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the sandbox data isolation and anonymization method as described in any one of claims 1 to 7 is implemented.

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