Software development data security management method based on cloud service

Abstract

The invention discloses a software development data security management method based on cloud service. S1, a multi-layer encryption and dynamic key management method; s2, a refined and adaptive access control method; s3, a deep data desensitization and anonymization processing method; s4, an omnibearing real-time monitoring and intelligent auditing method is adopted; s5, an efficient and flexible data backup and disaster recovery method; the invention relates to the technical field of cloud computing and information security, through integration of strategies such as multi-layer encryption, fine access control, deep data desensitization, omnibearing real-time monitoring, efficient data backup and continuous security training, the security, compliance and efficiency of data in the software development process are remarkably improved, and the security training and cultural construction method is suitable for the cloud computing and information security. According to the method, the risks of data leakage, illegal access and the like are effectively prevented, and development interruption and cost waste caused by data loss or system faults are reduced.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing and information security technology, and in particular to a method for managing software development data security based on cloud services. Background Art

[0002] In the wave of digital transformation, cloud computing has become an important engine driving the development of the software development industry. Its characteristics of on-demand resource allocation, high scalability and flexible deployment have greatly accelerated the iteration speed of software development, reduced costs, and improved development efficiency. However, as more and more software development projects migrate to cloud environments, data security issues have become increasingly prominent, becoming a bottleneck restricting the further popularization and in-depth application of cloud computing.

[0003] Traditional data security solutions often focus on single-point protection, such as network firewalls and intrusion detection systems. These measures are inadequate in the face of complex security threats in cloud service environments. Cloud services are distributed, virtualized, and multi-tenant, which makes data flow and sharing more frequent, and the attack surface also expands. At the same time, the compatibility and standard differences between cloud service providers also increase the difficulty of data protection.

[0004] In the process of software development, data runs through the entire life cycle, from requirements analysis, design, coding, testing to deployment and maintenance. Each link may involve the processing of sensitive data. Therefore, it is crucial to ensure data security throughout the entire life cycle of software development. However, the existing data security management methods do not have advanced encryption technology that can resist the increasingly enhanced encryption cracking capabilities. The access control mechanism is not sophisticated enough to implement the principle of least privilege. Data desensitization and anonymization processing is not in-depth enough to effectively protect user privacy. The real-time monitoring and auditing systems are not comprehensive enough to detect potential security threats. The data backup and disaster recovery mechanisms are not flexible enough to cope with the impact of emergencies. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a software development data security management method based on cloud services, which solves the problem that the security protection in the prior art is not strong enough.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A software development data security management method based on cloud services, specifically comprising the following steps:

[0007] S1. Multi-layer encryption and dynamic key management method;

[0008] S2, refined and adaptive access control method;

[0009] S3, deep data desensitization and anonymization processing methods;

[0010] S4, all-round real-time monitoring and intelligent auditing methods;

[0011] S5. Efficient and flexible data backup and disaster recovery methods;

[0012] S6. Continuous safety training and culture building methods;

[0013] Preferably, the multi-layer encryption and dynamic key management method in S1 specifically implements end-to-end encryption protection for sensitive data by introducing a multi-layer encryption mechanism, combining transport layer security and storage layer encryption, and implementing a dynamic key management strategy. The key management system is used in combination with a hardware security module to realize automatic generation, secure storage, dynamic distribution and regular replacement of keys, thereby ensuring the security and unpredictability of the keys.

[0014] Preferably, the refined and adaptive access control method in S2 achieves more refined permission allocation and management by combining a role-based access control model with attribute-based access control, ensuring that users can only obtain the minimum set of permissions required to complete their work, and introduces machine learning algorithms to analyze user behavior patterns, automatically identify and respond to abnormal access behaviors, and achieve adaptive adjustment of access control.

[0015] Preferably, the deep data desensitization and anonymization processing method in S3 adopts technologies such as deep learning and natural language processing to perform intelligent desensitization processing on sensitive data, retaining the data structure and characteristics while removing or replacing key information. At the same time, for data sets that need to be made public, an anonymization algorithm is used to ensure that the data cannot be traced back to a specific individual or organization while maintaining its statistical characteristics.

[0016] Preferably, the all-round real-time monitoring and intelligent auditing method in S4 is based on the deployment of an all-round real-time monitoring system, covering various links such as data transmission, storage, processing, and sharing, to achieve real-time monitoring and early warning of data access and operation behaviors, and at the same time introduce big data analysis and artificial intelligence technologies to perform intelligent analysis and mining of massive log data, quickly identify potential security threats and abnormal behavior patterns, and finally establish an intelligent auditing platform to provide visual audit reports and risk assessments to provide support for security decisions.

[0017] Preferably, the efficient and flexible data backup and disaster recovery method in S5 specifically includes the following steps:

[0018] A1. Develop flexible and diverse data backup strategies, including full backup, incremental backup, differential backup, etc., to ensure data integrity and recoverability;

[0019] A2. Establish a disaster recovery system across regions and cloud service providers to ensure that data and services can be quickly restored in the event of emergencies such as natural disasters and technical failures.

[0020] Preferably, the continuous security training and culture building method in S6 is specifically: providing regular security training and practical exercises based on the development team, covering the latest security threats, defense technologies, compliance requirements, etc., to enhance the team's security awareness and response capabilities.

[0021] Preferably, the continuous security training and culture building method in S6 is specifically: providing regular security training and practical exercises based on the development team, covering the latest security threats, defense technologies, compliance requirements, etc., to enhance the team's security awareness and response capabilities.

[0022] Preferably, the adaptation-based software source architecture in S1 is a single server and cluster architecture, and the matching degree of its operation data security management method is controlled by the performance of the operation processor.

[0023] Preferably, S6 also includes a self-protection method for user groups, which is specifically: when the system is invaded, multiple ports input data simultaneously, causing the main computing program to overload, thereby further causing the system to crash. After this situation occurs suddenly, an artificial port is intervened, and the user group self-examines the port input data to prevent all data intervention that causes the system to crash, and at the same time repair the system architecture to restore normal operation.

[0024] According to the cloud service-based software development data security management method of claim 1, it is characterized in that: the cloud service software includes IaaS, PaaS and SaaS, and the management method can be accessed in the early stage of construction of this type of cloud service software to change the internal system personnel and working methods of the software service to achieve a high degree of matching.

[0025] The fully enhanced cloud-based software development data security optimization management method of the present invention significantly improves the security, compliance and efficiency of data in the software development process by integrating strategies such as multi-layer encryption, fine access control, deep data desensitization, all-round real-time monitoring, efficient data backup and continuous security training. This method not only effectively prevents risks such as data leakage and illegal access, but also reduces development interruptions and cost waste caused by data loss or system failures. At the same time, it promotes technological innovation and lays a solid foundation for the sustainable development of the software development industry in a cloud service environment. Through this management method, enterprises can more confidently use cloud services for software development, accelerate product iterations, and enhance market competitiveness, while ensuring that user privacy and data security are fully protected. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Flow chart of the working principle of the present invention. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] See also Figure 1 , the embodiment of the present invention provides a technical solution: a software development data security management method based on cloud services, specifically comprising the following steps;

[0029] S1. Multi-layer encryption and dynamic key management method;

[0030] S2, refined and adaptive access control method;

[0031] S3, deep data desensitization and anonymization processing methods;

[0032] S4, all-round real-time monitoring and intelligent auditing methods;

[0033] S5. Efficient and flexible data backup and disaster recovery methods;

[0034] S6. Continuous safety training and culture building methods;

[0035] In the present invention, multi-layer encryption technology is adopted in S1 to ensure the security of data during transmission and storage. First, the transport layer security (TLS) protocol is used to encrypt network communications to prevent data from being intercepted or tampered with during transmission. Secondly, at the data storage level, high-intensity encryption algorithms such as AES-256 are used to encrypt data to ensure that even if the data is illegally obtained, it cannot be easily decrypted. At the same time, combined with the dynamic key management strategy, the key management system (KMS) and hardware security module (HSM) are used to realize automatic generation, secure storage, dynamic distribution and regular replacement of keys, ensuring the security and unpredictability of keys, thereby further enhancing the encryption protection of data.

[0036] In the present invention, the refined and adaptive access control method in S2 achieves more refined permission allocation and management by combining the role-based access control model with the attribute-based access control, ensuring that users can only obtain the minimum permission set required to complete their work, and introduces a machine learning algorithm to analyze user behavior patterns, automatically identify and respond to abnormal access behaviors, and achieve adaptive adjustment of access control. In order to implement the principle of least privilege, different permission sets are assigned to different roles, and permissions are dynamically adjusted according to user attributes and contextual environment to ensure that users can only access the minimum data set required to complete their work, automatically identify and respond to abnormal access behaviors, such as unauthorized access attempts, data tampering, etc., to achieve adaptive adjustment of access control and further improve the security protection capabilities of the system.

[0037] In the present invention, the deep data desensitization and anonymization processing method in S3 adopts technologies such as deep learning and natural language processing to perform intelligent desensitization processing on sensitive data, and removes or replaces key information while retaining the data structure and characteristics. At the same time, for data sets that need to be made public, an anonymization algorithm is used to ensure that the data cannot be traced back to a specific individual or organization while maintaining statistical characteristics. In order to protect user privacy and sensitive information, by identifying sensitive fields and key information in the data, replacement, blurring or deletion is used to remove or replace key information while retaining the data structure and characteristics. For data sets that need to be made public, advanced anonymization algorithms are used to ensure that the data cannot be traced back to a specific individual or organization while maintaining statistical characteristics. These measures help prevent data leakage and abuse and protect user privacy.

[0038] In the present invention, the all-round real-time monitoring and intelligent auditing method in S4 is based on the deployment of an all-round real-time monitoring system, covering various links such as data transmission, storage, processing, and sharing, to achieve real-time monitoring and early warning of data access and operation behaviors, and at the same time introduce big data analysis and artificial intelligence technology to intelligently analyze and mine massive log data, quickly identify potential security threats and abnormal behavior patterns, and finally establish an intelligent auditing platform to provide visual audit reports and risk assessments to provide support for security decisions. In order to timely discover and respond to potential security threats and abnormal behaviors, this method deploys an all-round real-time monitoring system, which covers various links such as data transmission, storage, processing, and sharing, to achieve real-time monitoring and early warning of data access and operation behaviors, quickly identify potential security threats and abnormal behavior patterns, and provide support for security decisions. These measures help enterprises to timely discover and respond to security threats and ensure the safety and controllability of the software development process.

[0039] The present invention, the efficient and flexible data backup and disaster recovery method in S5 specifically includes the following steps:

[0040] A1. Develop flexible and diverse data backup strategies, including full backup, incremental backup, differential backup, etc., to ensure data integrity and recoverability;

[0041] A2. Establish a disaster recovery system across regions and cloud service providers to ensure that data and services can be quickly restored in the event of natural disasters, technical failures and other emergencies. In order to ensure the integrity and recoverability of data, flexible and diverse data backup strategies have been formulated. These strategies include full backup, incremental backup and differential backup, which can be flexibly selected and configured according to business needs and data importance. At the same time, establish a disaster recovery system across regions and cloud service providers to ensure that data and services can be quickly restored in the event of natural disasters, technical failures and other emergencies. These measures help reduce the impact of data loss or system failures on corporate business and ensure the continuity and stability of software development.

[0042] In the present invention, the method for continuous security training and culture building in S6 is specifically as follows: providing regular security training and actual combat exercises based on the development team, covering the latest security threats, defense technologies, compliance requirements and other contents, to enhance the team's security awareness and response capabilities. In order to enhance the security awareness and response capabilities of the development team, this method emphasizes continuous security training and culture building. By regularly holding security training activities, actual combat exercises and case analysis, the development team is taught the latest security threats, defense technologies, compliance requirements and other knowledge. At the same time, a corporate culture atmosphere with security as the core is established, and employees' enthusiasm and participation in security work are stimulated through internal publicity, security competitions and commendations and rewards. These measures help to build a security protection system with full participation and provide solid security guarantees for the software development process.

[0043] The present invention, the continuous security training and culture building method in S6 is specifically: providing regular security training and practical exercises based on the development team, covering the latest security threats, defense technologies, compliance requirements and other contents, to enhance the team's security awareness and response capabilities.

[0044] In the present invention, the software source architecture based on adaptation in S1 is a single server and cluster architecture, and the matching degree of its operation data security management method is controlled by the performance of the operation processor.

[0045] The present invention, S6 also includes a self-protection method for user groups, which is specifically: when the system is invaded, multiple ports simultaneously input data, causing the main computing program to overload, thereby further causing the system to crash. After this situation occurs suddenly, an artificial port is intervened, and the user group self-examines the port input data to prevent all data intervention that causes the system to crash, and at the same time repair the system architecture to restore normal operation.

[0046] In the present invention, cloud service software includes IaaS, PaaS and SaaS, and this type of cloud service software can be connected to the management method in the early stage of construction to change the internal system personnel and working methods of the software service to achieve a high degree of matching.

[0047] The cloud service software is encrypted and protected through the above method to achieve security protection.

Claims

1. Software development data security management method based on cloud services, It is characterized in that Specifically include the following steps: S1. Multi-layer encryption and dynamic key management method; S2, refined and adaptive access control method; S3, deep data desensitization and anonymization processing methods; S4, all-round real-time monitoring and intelligent auditing methods; S5. Efficient and flexible data backup and disaster recovery methods; S6. Continuous safety training and culture building methods.

2. The method for managing software development data security based on cloud services according to claim 1, Features: The multi-layer encryption and dynamic key management method in S1 specifically implements end-to-end encryption protection for sensitive data by introducing a multi-layer encryption mechanism, combining transport layer security and storage layer encryption, and implementing a dynamic key management strategy. The key management system is combined with a hardware security module to realize automatic generation, secure storage, dynamic distribution and regular replacement of keys, thereby ensuring the security and unpredictability of keys.

3. The method for secure management of software development data based on cloud services according to claim 1, Features: The refined and adaptive access control method in S2 combines the role-based access control model with the attribute-level access control to achieve more refined permission allocation and management, ensuring that users can only obtain the minimum set of permissions required to complete their work, and introduces machine learning algorithms to analyze user behavior patterns, automatically identify and respond to abnormal access behaviors, and achieve adaptive adjustment of access control.

4. The method for managing software development data security based on cloud services according to claim 1, Features: The deep data desensitization and anonymization processing method in S3 uses technologies such as deep learning and natural language processing to perform intelligent desensitization on sensitive data, retaining the data structure and characteristics while removing or replacing key information. At the same time, for data sets that need to be made public, anonymization algorithms are used to ensure that the data cannot be traced back to specific individuals or organizations while maintaining statistical characteristics.

5. The method for secure management of software development data based on cloud services according to claim 1, Features: The all-round real-time monitoring and intelligent auditing method in S4 is based on the deployment of an all-round real-time monitoring system, covering various links such as data transmission, storage, processing, and sharing, to achieve real-time monitoring and early warning of data access and operation behaviors. At the same time, big data analysis and artificial intelligence technologies are introduced to intelligently analyze and mine massive log data, quickly identify potential security threats and abnormal behavior patterns, and finally establish an intelligent auditing platform to provide visual audit reports and risk assessments to provide support for security decisions.

6. The method for managing software development data security based on cloud services according to claim 1, Features: The efficient and flexible data backup and disaster recovery method in S5 specifically includes the following steps: A1. Develop flexible and diverse data backup strategies, including full backup, incremental backup, differential backup, etc., to ensure data integrity and recoverability; A2. Establish a disaster recovery system across regions and cloud service providers to ensure that data and services can be quickly restored in the event of emergencies such as natural disasters and technical failures.

7. The method for secure management of software development data based on cloud services according to claim 1, Features: The specific methods of continuous security training and culture building in S6 are: providing regular security training and practical exercises to the development team, covering the latest security threats, defense technologies, compliance requirements, etc., to enhance the team's security awareness and response capabilities.

8. The cloud service-based software development data security management method according to claim 1, Features: The adaptation-based software source architecture in S1 is a single server and cluster architecture, and the matching degree of its operation data security management method is controlled by the operation processor performance.

9. The method for secure management of software development data based on cloud services according to claim 1, Features: The S6 also includes a self-protection method for the user group, which is specifically: when the system is invaded, multiple ports input data simultaneously, causing the main computing program to overload, thereby further causing the system to crash. After this situation occurs suddenly, an artificial port is intervened, and the user group self-examines the port input data to prevent all data intervention that causes the system to crash, and at the same time repair the system architecture to restore normal operation.

10. The method for secure management of software development data based on cloud services according to claim 1, Features: The cloud service software includes IaaS, PaaS and SaaS, and this type of cloud service software can be connected to the management method in the early stage of construction to change the internal system personnel and working methods of the software service to achieve a high degree of matching.

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