Internet of Things service management system based on regional digital economy

Abstract

The invention discloses an Internet of Things service management system based on regional digital economy, and relates to the technical field of data processing. The Internet of Things service management system based on regional digital economy comprises a data minimization and anonymization module, an end-to-end encryption module, an access control and identity authentication module, a data security and auditing module and a security management and response module, and the data minimization and anonymization module is used for collecting personal sensitive information data; the end-to-end encryption module is used for encrypting a personal sensitive information data transmission process; the access control and identity authentication module is used for multi-factor authentication; the data security and audit module is used for protecting personal sensitive information data; and the security management and corresponding module is used for dynamically adjusting security policies and measures according to the privacy security state evaluation value. The problem that in the prior art, as the number of devices increases, more and more personal data are collected, and once sensitive data are integrated and analyzed, personal privacy may be exposed is solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an Internet of Things service management system based on regional digital economy. Background Art

[0002] With the advent of the digital age and the rapid development of information technology, data security and privacy protection have become the focus of global attention. Organizations and individuals are facing increasingly complex data protection challenges, especially when dealing with sensitive information. The security of personal sensitive information is not only related to the protection of user privacy rights.

[0003] In existing technologies, although a variety of security measures have been widely used, such as data encryption, access control, data anonymization, differential privacy technology, and homomorphic encryption, these measures often operate independently and lack a unified evaluation and management framework to comprehensively monitor and evaluate the comprehensive effects of these security measures. In addition, many existing security systems use static security strategies that are difficult to adapt to the ever-changing threat environment and technological development.

[0004] Therefore, in response to the above problems, an Internet of Things service management system based on the regional digital economy is urgently needed. Summary of the invention

[0005] Technical issues solved

[0006] In view of the shortcomings of the prior art, the present invention provides an Internet of Things service management system based on the regional digital economy, which solves the problem in the prior art that as the number of devices increases, more and more personal data is collected, and once sensitive data is integrated and analyzed, personal privacy may be exposed.

[0007] Technical Solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: an Internet of Things service management system based on regional digital economy, including a data minimization and anonymization module, an end-to-end encryption module, an access control and identity authentication module, a data security and audit module, and a security management and response module. The data minimization and anonymization module is used to collect personal sensitive information data, use data recognition technology to automatically scan personal sensitive information data, determine the data type, anonymize the personal sensitive information data, and obtain the data anonymization value; the end-to-end encryption module is used to encrypt the personal sensitive information data transmission process using the SSL / TLS encryption protocol, and use AES to encrypt the personal sensitive information data stored in the database and cloud environment to obtain the encryption technology strength value; the access control The identity authentication module is used to use passwords, biometric technology and mobile phone tokens for multi-factor authentication, set permission levels for different roles to access data, and obtain access control and identity authentication values; the data security and audit module is used to use differential privacy strategies and homomorphic encryption technologies to protect personal sensitive information data, perform system data audits, implement personal sensitive information data integrity verification measures, and obtain differential privacy implementation values, homomorphic encryption application values ​​and data integrity audit capability values; the security management and corresponding modules are used to obtain privacy security status evaluation values ​​through comprehensive calculation of data anonymization values, encryption technology strength values, access control and identity authentication values, differential privacy implementation values, homomorphic encryption application values ​​and data integrity audit capability values; and dynamically adjust security policies and measures according to the privacy security status evaluation values.

[0009] Furthermore, the specific process of collecting personal sensitive information data, using data identification technology to automatically scan personal sensitive information data, determining data type, anonymizing personal sensitive information data, and obtaining data anonymization value is: collecting personal sensitive information data, using data identification and classification tools to identify and classify personal sensitive information data, and using K-anonymization technology to anonymize personal sensitive data; monitoring the efficiency and coverage of the anonymization processing, recording the number of successfully anonymized data sets and the total number of data sets, and obtaining data anonymization value.

[0010] Furthermore, the specific process of obtaining the data anonymization value is: obtaining the number of successfully anonymized data sets and the total number of data sets, and obtaining the data anonymization value by calculating the ratio of the number of successfully anonymized data to the total number of data sets.

[0011] Furthermore, the personal sensitive information data transmission process is encrypted using the SSL / TLS encryption protocol, and the personal sensitive information data stored in the database and cloud environment is encrypted using AES. The specific process for obtaining the encryption technology strength value is: all outgoing and incoming personal sensitive information data are encrypted using the SSL / TLS encryption protocol, all communication channels are forced to encrypt, and any unencrypted data transmission is prohibited; the AES-256 encryption algorithm is implemented to encrypt all personal sensitive information data stored in databases and cloud storage facilities, encryption keys are updated regularly, and a key management system is used to securely store and manage keys; the number of encrypted data transmission and storage operations and the total number of data transmission and storage operations are recorded to obtain the encryption technology strength value.

[0012] Furthermore, the specific process of obtaining the encryption technology strength value is: obtaining the number of encrypted data transmission and storage operations and the total number of data transmission and storage operations, and obtaining the encryption technology strength value by calculating the ratio of the number of encrypted data transmission and storage operations to the total number of data transmission and storage operations.

[0013] Furthermore, the specific process of using passwords, biometric technology and mobile phone tokens for multi-factor authentication, setting permission levels for different roles to access data, and obtaining access control and identity authentication values ​​is as follows: using passwords, biometric technology and mobile phone tokens for multi-factor authentication, setting different levels of access rights for different roles, and auditing and recording all user activities; monitoring and recording the number of unauthorized access attempts that are successfully blocked and the total number of unauthorized access attempts, and obtaining access control and identity authentication values ​​by calculating the number of unauthorized access attempts that are successfully blocked and the total number of unauthorized access attempts.

[0014] Furthermore, the specific process of using differential privacy strategy and homomorphic encryption technology to protect personal sensitive information data, perform system data audits, and implement personal sensitive information data integrity verification measures is as follows: using differential privacy technology to protect personal sensitive information data, preventing information leakage by adding noise, and recording the number of data operations and the total number of data operations that implement differential privacy; using homomorphic encryption to allow direct calculations on encrypted personal sensitive information data, protecting data content from external applications, and recording the number of data processing using homomorphic encryption and the total number of data processing; running automated audit tools to track and record all access and modifications to personal sensitive information data, implementing integrity checks to ensure that personal sensitive information data has not been modified without authorization, using technologies such as blockchain to provide tamper-proof audit tracking, and recording the number of data integrity issues discovered and corrected and the total number of data integrity issues discovered.

[0015] Furthermore, the specific process of obtaining the differential privacy implementation value, homomorphic encryption application value and data integrity audit capability value is as follows: obtain the number of data operations that implement differential privacy and the total number of data operations, and obtain the differential privacy implementation value by calculating the ratio of the number of data operations that implement differential privacy to the total number of data operations; obtain the number of data processing using homomorphic encryption and the total number of data processing, and obtain the homomorphic encryption application value by calculating the ratio of the number of data processing using homomorphic encryption and the total number of data processing; obtain the number of data processing using homomorphic encryption and the total number of data processing, and obtain the data integrity audit capability value by calculating the number of data processing using homomorphic encryption and the total number of data processing.

[0016] Furthermore, the specific calculation formula of the privacy security status evaluation value is:

[0017] In the formula, PSS represents the privacy security status evaluation value, x D represents the data anonymization value, w D Represents the weight coefficient of the data anonymization value, α D Represents the impact index of data anonymization value, x E Indicates the encryption technology strength value, w E The weight coefficient representing the encryption technology strength value, α E Indicates the impact index of the encryption technology strength value, x A Indicates access control and identity authentication value, w A Represents the weight coefficient of access control and identity authentication value, α A represents the impact index of access control and identity authentication value, x P represents the differential privacy implementation value, w P The weight coefficient representing the differential privacy enforcement value, α P represents the impact index of the differential privacy implementation value, x H Represents the homomorphic encryption application value, w H Represents the weight coefficient of the homomorphic encryption application value, α H Represents the impact index of homomorphic encryption application value, x I Indicates the data integrity audit capability value, w I The weight coefficient representing the data integrity audit capability value, α I Represents the impact index of the data integrity audit capability value, x i represents the value of the i-th technical measure, w ij represents the weight of the interaction effect between the i-th and j-th technical measures, x i ·x j Expresses the product of different safety measure values.

[0019] Furthermore, the dynamic adjustment of security policies and measures according to the privacy security status evaluation value is specifically as follows: comparing the privacy security status evaluation value with the threshold in real time; when the privacy security status evaluation value is lower than the threshold, immediately conducting a security review, identifying security weaknesses, strengthening access control in access control and identity authentication modules, and improving the encryption standard of the end-to-end encryption module; when the privacy security status evaluation value is greater than or equal to the threshold, maintaining regular security checks and vulnerability scans, and continuing to execute current security policies and measures.

[0020] Beneficial Effects

[0021] The present invention has the following beneficial effects:

[0022] (1) This IoT service management system based on the regional digital economy provides comprehensive protection for personal sensitive information by integrating data minimization and anonymization, end-to-end encryption, access control and authentication, differential privacy, homomorphic encryption technology, and comprehensive data security and audit modules. This achieves all-round security and privacy protection for personal data, and effectively solves the problem that the scattered security measures in the existing technology cannot fully cover all security threats.

[0023] (2) The IoT service management system based on regional digital economy dynamically adjusts security policies and measures according to the privacy security status evaluation value. This achieves real-time optimization and self-adjustment of security measures, effectively solving the problem that static security policies in existing technologies cannot quickly adapt to new threats and changing environments.

[0024] (3) The IoT service management system based on the regional digital economy can quickly locate security vulnerabilities and risk points by real-time monitoring and evaluating the privacy security status assessment value. This can achieve rapid identification and response to potential threats, effectively solving the problem of slow and inefficient risk assessment and response processes in existing technologies.

[0025] (4) This IoT service management system based on the regional digital economy strengthens data privacy protection and improves the transparency and compliance of data governance by adopting automated data identification and classification tools and K-anonymization technology. This achieves more efficient and transparent data management and effectively solves the problem that data processing in existing technologies is difficult to meet strict privacy standards and regulatory requirements.

[0026] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a structural diagram of the Internet of Things service management system based on regional digital economy in the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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.

[0029] See also Figure 1 The embodiment of the present invention provides a technical solution: an Internet of Things service management system based on regional digital economy, including a data minimization and anonymization module, an end-to-end encryption module, an access control and identity authentication module, a data security and audit module, and a security management and response module. The data minimization and anonymization module is used to collect personal sensitive information data, automatically scan personal sensitive information data using data recognition technology, determine the data type, anonymize personal sensitive information data, and obtain data anonymization value; the end-to-end encryption module is used to encrypt the personal sensitive information data transmission process using the SSL / TLS encryption protocol, and encrypt the personal sensitive information data stored in the database and cloud environment using AES to obtain the encryption technology strength value; access control and identity authentication The module is used to use passwords, biometric technology and mobile phone tokens for multi-factor authentication, set permission levels for different roles to access data, and obtain access control and identity authentication values; the data security and audit module is used to use differential privacy strategies and homomorphic encryption technology to protect personal sensitive information data, perform system data audits, implement personal sensitive information data integrity verification measures, and obtain differential privacy implementation values, homomorphic encryption application values ​​and data integrity audit capability values; the security management and corresponding modules are used to obtain privacy security status assessment values ​​through comprehensive calculation of data anonymization values, encryption technology strength values, access control and identity authentication values, differential privacy implementation values, homomorphic encryption application values ​​and data integrity audit capability values; and dynamically adjust security policies and measures according to the privacy security status assessment values.

[0030] Specifically, personal sensitive information data is collected, personal sensitive information data is automatically scanned using data identification technology, the data type is determined, personal sensitive information data is anonymized, and the data anonymization value is obtained. The specific process is: first, advanced data identification and classification tools are used to accurately identify and classify the collected data. This process is not only fast and efficient, but also ensures that all sensitive data has been correctly identified and classified before processing. Then, the system uses K-anonymization technology to anonymize these sensitive data. This technology uses generalization and suppression methods to ensure that the data retains its purpose while minimizing the risk exposure of personally identifiable information.

[0031] Furthermore, the system will monitor the efficiency and coverage of the anonymization process. This monitoring ensures the efficiency of the process and verifies the widespread application of anonymization measures. Specifically, the system will record the number of data sets that have been successfully anonymized and the number of total data sets. This statistic not only reflects the scope of implementation of anonymization measures, but also provides a data basis for further security analysis. Finally, by calculating the ratio of successfully anonymized data sets to the total data set, the system is able to generate an accurate data anonymization value.

[0032] In this implementation scheme, first, by using advanced data identification and classification tools, the system can accurately identify and classify the collected personal sensitive information, ensuring the pertinence and accuracy of the processing process. Subsequently, the K-anonymization technology is applied to anonymize these sensitive data, effectively reducing the risk of personal privacy being leaked when the data is made public or shared. This technology ensures a balance between data availability and personal privacy by generalizing or suppressing information, thereby maximizing user privacy while retaining the value of data analysis. In addition, by monitoring the efficiency and coverage of the anonymization process and recording the number of successfully anonymized data sets, the system can evaluate the implementation effect of the anonymization measures and optimize the data protection strategy accordingly, thereby ensuring the transparency and reliability of the entire data processing process. In short, this step not only improves the security standards of data processing, but also enhances the compliance of organizations with data protection regulations.

[0033] Specifically, the specific process of obtaining the data anonymization value is as follows: First, the system needs to accurately record the number of data sets that have been successfully anonymized. This includes all data sets processed by K-anonymization technology and meet the predetermined privacy protection standards. Secondly, the system also needs to count the total number of data sets before processing, that is, the number of all original data sets collected and prepared for anonymization. By comparing the number of successfully anonymized data sets with the total number of data sets, we can calculate the percentage of successfully anonymized data sets in the total data sets.

[0034] In this implementation, the data anonymization value directly reflects the coverage and efficiency of the anonymization measures, thereby providing a quantitative evaluation of the effectiveness of data privacy protection. This method not only helps to confirm the implementation quality of data protection measures, but also promotes the continuous improvement and optimization of privacy protection strategies.

[0035] Specifically, the personal sensitive information data transmission process is encrypted using the SSL / TLS encryption protocol, and the personal sensitive information data stored in the database and cloud environment is encrypted using AES. The specific process of obtaining the encryption technology strength value is as follows: First, all outgoing and incoming personal sensitive information data are forcibly encrypted using the SSL / TLS encryption protocol to ensure that the data will not appear in plain text during any data transmission process, thereby effectively preventing the data from being stolen or tampered with during transmission. Secondly, the system uses the powerful AES-256 encryption algorithm to encrypt all personal sensitive information data stored in the database and cloud environment. In addition, to further enhance security, the system also regularly updates encryption keys and stores and manages these keys through a secure key management system to ensure the security and effectiveness of the keys.

[0036] Finally, to evaluate the effectiveness of encryption, the system records the number of encrypted data transfer and storage operations and the total number of data transfer and storage operations. By calculating the ratio of encrypted operations to the total number of operations, the encryption strength value can be obtained.

[0037] In this implementation scheme, the system significantly improves data security by using SSL / TLS encryption protocol and AES-256 encryption algorithm to encrypt the transmission and storage of personal sensitive information data. All outgoing and incoming data are forcibly encrypted, effectively preventing data leakage and tampering during transmission. At the same time, AES-256 encryption is implemented for data stored in databases and cloud environments, and the security protection of stored data is further strengthened by regularly updating keys and adopting a secure key management system. In addition, by recording and analyzing the number of encrypted data operations, the system is able to quantitatively evaluate the implementation strength and coverage of encryption technology, thereby ensuring the effective implementation of encryption measures. This series of measures not only strengthens data protection, but also enhances the organization's confidence in the implementation of security policies and ensures effective response to external threats and internal security challenges.

[0038] Specifically, the process of obtaining the encryption technology strength value is as follows: First, the system systematically collects and records the number of all encrypted data transmission and storage operations. This includes all transmission operations encrypted using the SSL / TLS protocol and data operations encrypted and stored in databases and cloud environments using the AES encryption algorithm. Second, the system also records the total number of data transmission and storage operations, regardless of whether these operations use encryption measures.

[0039] By comparing and calculating these data, the system can determine the proportion of encrypted data operations to total data operations. Specifically, by calculating the percentage of encrypted data transmission and storage operations to the total data transmission and storage operations, the system can derive the encryption technology strength value.

[0040] In this implementation, the encryption technology strength value directly reflects the popularity and execution quality of encryption measures, providing an important basis for further security policy adjustment and optimization. This method not only enhances data security, but also provides an effective tool to monitor and evaluate the implementation effect of encryption technology.

[0041] Specifically, using passwords, biometrics, and mobile phone tokens for multi-factor authentication, setting permission levels for different roles to access data, and obtaining access control and identity authentication values. The specific process is as follows:

[0042] First, the system implements a multi-factor authentication mechanism including passwords, biometrics, and mobile phone tokens. This authentication method greatly enhances the strength of security verification and ensures that only authorized users can access sensitive data within their authority. In addition, according to the user's role and responsibilities, the system sets different levels of access rights for different users, thereby achieving fine management of access to information resources.

[0043] The system also continuously audits all user activities through a comprehensive monitoring and recording mechanism, which includes recording of various operations such as successful logins, data access, data modification, etc. Furthermore, the system pays special attention to unauthorized access attempts by monitoring and recording the number of all such attempts. This includes not only the number of unauthorized access attempts that were successfully blocked, but also the total number of unauthorized access attempts that occurred. By collecting statistics and analyzing these two types of data, the system can calculate the blocking rate of unauthorized access attempts, that is, the ratio of the number of unauthorized access attempts that were successfully blocked to the total number of unauthorized access attempts, thereby obtaining a comprehensive performance indicator of access control and authentication - the access control and authentication value.

[0044] In this implementation scheme, the protection of sensitive information is effectively enhanced by implementing multi-factor authentication including passwords, biometrics and mobile phone tokens, as well as setting role-based access control. Multi-factor authentication improves the strength of security verification and significantly reduces the risk of unauthorized access. At the same time, by setting specific access rights for different roles, the system ensures the rational allocation and use of information resources, and prevents excessive permissions and data abuse. In addition, the system conducts detailed audits and records of all user activities, including successful and failed access attempts, which not only provides transparency of operations, but also enhances tracking and backtracking capabilities. In particular, by calculating the ratio of successfully blocked unauthorized access attempts to the total number of attempts, the system can quantitatively evaluate the effectiveness of access control and identity authentication. This measure not only improves the security of the system, but also provides data support for continuous security improvements, ensuring effective responses to existing and emerging threats.

[0045] Specifically, differential privacy strategies and homomorphic encryption technologies are used to protect personal sensitive information data, perform system data audits, and implement personal sensitive information data integrity verification measures. The specific process is as follows: First, the system protects personal sensitive information data by using differential privacy technology, which effectively prevents potential information leakage by adding noise to the data. In order to monitor the implementation of differential privacy strategies, the system records the number of data operations that implement differential privacy and the total number of data operations to ensure that all sensitive data processing activities meet privacy protection standards.

[0046] Furthermore, in order to process data while keeping it encrypted, the system uses homomorphic encryption technology. This allows data to be calculated without being decrypted, thereby protecting the data content from being misused or leaked by external applications. The system also records the number of data processed using homomorphic encryption and the total number of data processed to ensure the widespread application and effectiveness of encryption measures.

[0047] Finally, the system runs automated audit tools to track and record all access and modification operations of personal sensitive information data. In addition, in order to strengthen data security, data integrity checks are implemented to ensure that personal sensitive information data has not been modified without authorization. The use of technologies such as blockchain provides an unalterable audit trail, which not only enhances data security protection, but also improves the reliability and transparency of audits. The system also records the number of data integrity issues found and corrected and the total number of data integrity issues found. Through these measures, the system can effectively protect the security of personal sensitive information and ensure the integrity and transparency of data processing and storage processes.

[0048] In this implementation plan, the protection effect of personal sensitive information data is significantly improved by comprehensively applying differential privacy technology, homomorphic encryption technology and automated audit tools. Differential privacy technology effectively prevents information leakage and protects user privacy by adding noise to the data, while ensuring that the data can be used for analysis without exposing personal identity. Homomorphic encryption technology allows calculations to be performed while keeping the data encrypted, which not only ensures the confidentiality of the data but also allows the practicality of the data, and is particularly suitable for scenarios where sensitive data needs to be processed in a cloud environment. In addition, the system's automated audit tools comprehensively track all data access and modification activities, and achieve tamper-proof audit tracking through the use of technologies such as blockchain, greatly enhancing the integrity and security of the data. Through these measures, the system not only ensures the high security and privacy protection of sensitive data, but also improves the ability to respond to security threats, providing organizations with a highly reliable and transparent data processing environment.

[0049] Specifically, the specific process of obtaining the differential privacy implementation value, homomorphic encryption application value, and data integrity audit capability value is as follows: First, in order to calculate the differential privacy implementation value, the number of data operations that implement differential privacy technology and the total number of data operations performed are recorded. By comparing these two quantities, that is, the ratio of the number of data operations that implement differential privacy to the total number of data operations, the degree of implementation of differential privacy can be obtained. This ratio directly indicates the scope of application of differential privacy technology in data processing.

[0050] Next, by recording the number of data operations processed using homomorphic encryption technology and the total number of data processing operations, the ratio of the two is calculated to obtain the homomorphic encryption application value. This value can accurately reflect the security and practicality of homomorphic encryption technology in protecting the data processing process.

[0051] Finally, by counting the number of data processing operations using homomorphic encryption technology and the total number of data processing operations, and calculating the ratio of the two, we can obtain indicators of data audit integrity and effectiveness.

[0052] In this implementation plan, the differential privacy implementation value, homomorphic encryption application value, and data integrity audit capability value are evaluated through specific quantitative methods, effectively monitoring and evaluating the actual application effect of key data protection technologies. First, by calculating the ratio of the number of data operations that implement differential privacy technology to the total number of data operations, the system can clearly understand the coverage of differential privacy technology and ensure the widespread application of privacy protection measures. Similarly, the calculation of the homomorphic encryption application value provides direct evidence of the actual application degree of homomorphic encryption technology in daily data processing, reflecting its effectiveness in protecting data processing in an encrypted state. In addition, the evaluation of the data integrity audit capability value emphasizes the system's ability to ensure that data is not modified without authorization, and enhances the security monitoring of data operations. The calculation of these metrics not only confirms the effectiveness of the security measures taken, but also provides data support for further security policy adjustments, thereby ensuring that the system's data protection measures can continue to adapt to new security challenges.

[0053] Specifically, the calculation formula for the privacy security status evaluation value is:

[0054] In the formula, PSS represents the privacy security status assessment value, which is calculated by weighting various security technical measures, x D represents the data anonymization value, w D Represents the weight coefficient of the data anonymization value, α D Represents the impact index of data anonymization value, x E Indicates the encryption technology strength value, w E The weight coefficient representing the encryption technology strength value, α E Indicates the impact index of the encryption technology strength value, x A Indicates access control and identity authentication value, w A Represents the weight coefficient of access control and identity authentication value, α A represents the impact index of access control and identity authentication value, x P represents the differential privacy implementation value, w P The weight coefficient representing the differential privacy enforcement value, α P represents the impact index of the differential privacy implementation value, x H Represents the homomorphic encryption application value, w H Represents the weight coefficient of the homomorphic encryption application value, α H Represents the impact index of homomorphic encryption application value, x I Indicates the data integrity audit capability value, w I The weight coefficient representing the data integrity audit capability value, α I Represents the impact index of the data integrity audit capability value, x irepresents the value of the i-th technical measure, w ij represents the weight of the interaction effect between the i-th and j-th technical measures, x i ·x j It expresses the product of the values ​​of different safety measures. The value of each measure is determined by the effect value x of its implementation. i , the corresponding weight coefficient w i And the impact index α i Composition. Weight coefficient w i Usually depends on the contribution of the measure to the overall system security. These weight coefficients are usually between 0 and 1. Their specific values ​​can be determined through expert evaluation, historical data analysis or relative importance research. i It is used to adjust the influence of each technical measure value, reflecting the role of different security technologies in the protection system. It is usually obtained based on actual application experience or through security testing.

[0056] In addition, w in the formula ij represents the weight of the interaction effect between different technical measures, which takes into account the possible synergistic or offsetting effects of different security measures. For example, data anonymization and homomorphic encryption may have different security effects when applied simultaneously than when applied separately. The weight of these interaction effects w ij It also varies between 0 and 1 and needs to be accurately set based on actual application scenarios and effect tests;

[0057] In summary, this formula provides a quantitative assessment of system security by considering the individual impacts of each security technology and their interactions, enabling the security team to dynamically adjust and optimize security policies based on the assessment results to ensure that sensitive information is best protected.

[0058] In this implementation scheme, the privacy security status assessment value calculation formula provides an in-depth quantitative assessment of the overall system security by comprehensively considering the individual impacts of different security measures and their interactions. The setting of weight factors and impact indexes in the formula makes the assessment more accurate and can reflect the contribution of each technical measure to the overall security. In addition, by adding the calculation of interaction effects, the formula can also capture the possible synergy or offset effects between different security technologies, thereby providing a comprehensive security view. This evaluation method not only enhances the understanding of the effectiveness of existing security measures, but also supports data-driven decision-making processes, allowing security teams to adjust and optimize security policies based on real-time evaluation results to ensure that data protection measures keep pace with ever-changing security threats. Such a dynamic evaluation and adjustment mechanism greatly improves the organization's ability to combat information security threats and provides a more solid protection barrier for sensitive data.

[0059] Specifically, dynamically adjusting security policies and measures based on the privacy security status assessment value is as follows: real-time monitoring of the privacy security status assessment value and comparing it with the preset security threshold is a key step to ensure data security and timely response to potential threats. This process specifically includes: the system continuously calculates and monitors the privacy security status assessment value and compares it with the established threshold. When the privacy security status assessment value is lower than the threshold, this usually indicates that there are potential security risks in the system or that known security measures fail to provide adequate protection. In this case, the system will immediately initiate a security review procedure to quickly identify any security weaknesses. This review covers a comprehensive system inspection, including but not limited to access control and identity authentication modules, and the access control mechanisms of these modules will be strengthened to prevent unauthorized access. At the same time, the encryption standards of the end-to-end encryption module will also be improved to ensure that data security is strengthened during all data transmission and storage processes.

[0060] On the contrary, when the privacy security status assessment value is greater than or equal to the threshold, it means that the security of the system is in an ideal state or the security measures are having the expected effect, so the regular security monitoring procedures can be maintained. This includes performing regular security checks and vulnerability scans, and continuing to monitor and evaluate security vulnerabilities to ensure that any emerging threats can be discovered and handled in a timely manner. In addition, the system will continue to implement current security policies and measures to maintain the continuity and stability of security protection. This dynamic security management strategy enables the system to remain adaptable and flexible in a changing threat environment, thereby effectively protecting sensitive data from harm.

[0061] In this implementation scheme, by real-time monitoring and comparing the privacy security status evaluation value with the preset threshold, the system can effectively and dynamically adjust its security policy to adapt to changing security needs. When the privacy security status evaluation value is lower than the threshold, the system immediately conducts a security review to quickly identify and address security weaknesses, such as strengthening access control and improving encryption standards, which greatly reduces the risks posed by security vulnerabilities. Conversely, when the privacy security status evaluation value is equal to or higher than the threshold, the system maintains routine security checks and continuous monitoring to ensure that the implemented security measures remain effective and new potential threats are discovered in a timely manner. This response mechanism based on evaluation values ​​not only enhances the system's defense capabilities, but also improves the speed and efficiency of responding to security incidents, ensuring the continued security of data.

[0062] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants 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.

[0063] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An Internet of Things service management system based on regional digital economy, including a data minimization and anonymization module, an end-to-end encryption module, an access control and identity authentication module, a data security and audit module, and a security management and response module, characterized by: The data minimization and anonymization module is used to collect personal sensitive information data, automatically scan the personal sensitive information data using data recognition technology, determine the data type, anonymize the personal sensitive information data, and obtain the data anonymization value; The end-to-end encryption module is used to encrypt the personal sensitive information data transmission process using the SSL / TLS encryption protocol, and to encrypt the personal sensitive information data stored in the database and cloud environment using AES to obtain the encryption technology strength value; The access control and identity authentication module is used to use passwords, biometrics and mobile phone tokens for multi-factor authentication, set permission levels for different roles to access data, and obtain access control and identity authentication values; The data security and audit module is used to protect personal sensitive information data using differential privacy strategies and homomorphic encryption technology, perform system data audits, implement personal sensitive information data integrity verification measures, and obtain differential privacy implementation values, homomorphic encryption application values, and data integrity audit capability values; The security management and corresponding modules are used to obtain a privacy security status assessment value by comprehensive calculation through data anonymization value, encryption technology strength value, access control and identity authentication value, differential privacy implementation value, homomorphic encryption application value and data integrity audit capability value; Dynamically adjust security policies and measures based on privacy security status assessment values.

2. The Internet of Things service management system based on regional digital economy according to claim 1 is characterized in that: The specific process of collecting personal sensitive information data, automatically scanning personal sensitive information data using data recognition technology, determining the data type, anonymizing personal sensitive information data, and obtaining the data anonymization value is as follows: Collect personal sensitive information data, use data identification and classification tools to identify and classify personal sensitive information data, and use K-anonymization technology to anonymize personal sensitive data; Monitor the efficiency and coverage of the anonymization process, record the number of successfully anonymized data sets and the total number of data sets, and obtain the data anonymization value.

3. The Internet of Things service management system based on regional digital economy according to claim 2 is characterized in that: The specific process of obtaining the data anonymization value is as follows: The number of successfully anonymized data sets and the total number of data sets are obtained, and the data anonymization value is obtained by calculating the ratio of the number of successfully anonymized data to the total number of data sets.

4. The Internet of Things service management system based on regional digital economy according to claim 1 is characterized in that: The personal sensitive information data transmission process is encrypted using the SSL / TLS encryption protocol, and the personal sensitive information data stored in the database and cloud environment is encrypted using AES. The specific process of obtaining the encryption technology strength value is as follows: All outgoing and incoming personal sensitive information data is encrypted through SSL / TLS encryption protocol, and all communication channels are forced to be encrypted, prohibiting any unencrypted data transmission; Implement AES-256 encryption algorithm to encrypt all personal sensitive information stored in databases and cloud storage facilities, regularly update encryption keys, and use a key management system to securely store and manage keys; Record the number of encrypted data transmission and storage operations and the total number of data transmission and storage operations to obtain the encryption technology strength value.

5. The Internet of Things service management system based on regional digital economy according to claim 4 is characterized in that: The specific process of obtaining the encryption technology strength value is as follows: The number of encrypted data transmission and storage operations and the total number of data transmission and storage operations are obtained, and the encryption technology strength value is obtained by calculating the ratio of the number of encrypted data transmission and storage operations to the total number of data transmission and storage operations.

6. The Internet of Things service management system based on regional digital economy according to claim 1 is characterized in that: The specific process of using passwords, biometrics, and mobile phone tokens for multi-factor authentication, setting permission levels for different roles to access data, and obtaining access control and identity authentication values ​​is as follows: Use passwords, biometrics, and mobile phone tokens for multi-factor authentication, set different levels of access rights for different roles, and audit and record all user activities; Monitor and record the number of successfully blocked unauthorized access attempts and the total number of unauthorized access attempts, and obtain access control and identity authentication values ​​by calculating the number of successfully blocked unauthorized access attempts and the total number of unauthorized access attempts.

7. The Internet of Things service management system based on regional digital economy according to claim 1 is characterized in that: The specific process of using differential privacy strategy and homomorphic encryption technology to protect personal sensitive information data, perform system data audit, and implement personal sensitive information data integrity verification measures is as follows: Use differential privacy technology to protect personal sensitive information data, add noise to prevent information leakage, and record the number of data operations that implement differential privacy and the total number of data operations; Homomorphic encryption allows direct calculations on encrypted personal sensitive information data, protects data content from external applications, and records the number of data processed using homomorphic encryption and the total number of data processed; Run automated audit tools to track and record all access and modifications to personal sensitive information data, implement integrity checks to ensure that personal sensitive information data has not been modified without authorization, use technologies such as blockchain to provide tamper-proof audit trails, and record the number of data integrity issues discovered and corrected and the total number of data integrity issues discovered.

8. The Internet of Things service management system based on regional digital economy according to claim 1, characterized in that: The specific process of obtaining the differential privacy implementation value, homomorphic encryption application value and data integrity audit capability value is as follows: Obtain the number of data operations implementing differential privacy and the total number of data operations, and calculate the differential privacy implementation value by calculating the ratio of the number of data operations implementing differential privacy to the total number of data operations; Obtain the number of data processed using homomorphic encryption and the total number of data processed, and calculate the ratio of the number of data processed using homomorphic encryption to the total number of data processed to obtain the homomorphic encryption application value; The number of data processed using homomorphic encryption and the total number of data processed are obtained, and the data integrity audit capability value is obtained by calculating the number of data processed using homomorphic encryption and the total number of data processed.

9. The Internet of Things service management system based on regional digital economy according to claim 1, characterized in that: The specific calculation formula of the privacy security status evaluation value is: In the formula, PSS represents the privacy security status evaluation value, x D represents the data anonymization value, w D Represents the weight coefficient of the data anonymization value, α D Represents the impact index of data anonymization value, x E Indicates the encryption technology strength value, w E The weight coefficient representing the encryption technology strength value, α E Indicates the impact index of the encryption technology strength value, x A Indicates access control and identity authentication value, w A Represents the weight coefficient of access control and identity authentication value, α A represents the impact index of access control and identity authentication value, x P represents the differential privacy implementation value, w P The weight coefficient representing the differential privacy enforcement value, αP 表 The impact index of differential privacy implementation value, x H Represents the homomorphic encryption application value, w H Represents the weight coefficient of the homomorphic encryption application value, α H Represents the impact index of homomorphic encryption application value, x I Indicates the data integrity audit capability value, w I The weight coefficient representing the data integrity audit capability value, α I Represents the impact index of the data integrity audit capability value, x i represents the value of the i-th technical measure, w ij represents the weight of the interaction effect between the i-th and j-th technical measures, x i ·x j Expresses the product of different safety measure values.

10. The Internet of Things service management system based on regional digital economy according to claim 1, characterized in that: The dynamic adjustment of security policies and measures according to the privacy security status evaluation value is specifically as follows: Compare the privacy and security status assessment value with the threshold in real time. When the privacy and security status assessment value is lower than the threshold, immediately conduct a security review to identify security weaknesses, strengthen access control in the access control and identity authentication modules, and improve the encryption standard of the end-to-end encryption module; When the privacy security status assessment value is greater than or equal to the threshold, maintain regular security checks and vulnerability scans, and continue to implement current security policies and measures.

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