Data destruction method and device and electronic equipment

Abstract

The invention provides a data destruction method and device and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring to-be-processed data; analyzing the to-be-processed data to obtain an analysis result; if the analysis result indicates that the to-be-processed data is sensitive data, destroying the to-be-processed data in an encrypted storage mode; and if the analysis result indicates that the to-be-processed data is periodic data, destroying the to-be-processed data by modifying a data state. By implementing the technical scheme provided by the invention, rationalization of data destruction is facilitated.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and in particular to a data destruction method, device and electronic device. Background Art

[0002] In the current field of data processing and storage, data destruction is a crucial but often overlooked link.

[0003] At present, there are often many unreasonable aspects in the data destruction process in the existing technology. These problems not only threaten the security of personal privacy, but also affect the compliance and efficiency of enterprise data management. Moreover, traditional methods mostly rely on simple deletion operations, such as deleting records from the database or clearing files. Therefore, the above methods can neither effectively protect the security of sensitive data nor achieve the reasonable management and utilization of periodic data, which is not conducive to the rationalization of data destruction.

[0004] Therefore, a data destruction method, device and electronic device are urgently needed. Summary of the invention

[0005] The present application provides a data destruction method, device and electronic device to facilitate the rationalization of data destruction.

[0006] In a first aspect of the present application, a data destruction method is provided, the method comprising: obtaining data to be processed; analyzing the data to be processed to obtain an analysis result; if the analysis result indicates that the data to be processed is sensitive data, destroying the data to be processed by encrypting and storing it; if the analysis result indicates that the data to be processed is periodic data, destroying the data to be processed by modifying the data state.

[0007] By adopting the above technical solution, for sensitive data, the destruction by encrypted storage is actually converted into a state that cannot be easily read or restored. This method effectively prevents the risk of illegal recovery and leakage of sensitive data after deletion, thereby improving data security. The encryption process ensures that even if the storage medium is lost or stolen, unauthorized third parties cannot obtain the original data content. This method automatically distinguishes between sensitive data and periodic data by intelligently analyzing the nature of the data to be processed, and adopts corresponding destruction strategies. This automated processing method reduces the need for manual intervention and improves the efficiency of data management. In particular, it can significantly reduce time and labor costs when processing large amounts of data. In many industries and regions, data protection regulations require enterprises and organizations to take reasonable measures to protect personal privacy and sensitive information. This method helps enterprises and organizations meet these compliance requirements and avoid possible legal risks and fines by encrypting and storing sensitive data and managing periodic data reasonably. For periodic data, it is destroyed by modifying the data state instead of directly deleting it, retaining some traces or metadata of the data. The advantage of this is that data audits or historical analysis can be performed when necessary without worrying about the complete loss of data. Therefore, the above method facilitates the rationalization of data destruction.

[0008] Optionally, the obtaining of the data to be processed specifically includes: obtaining original data; preprocessing the original data to obtain the data to be processed, wherein the preprocessing includes denoising, filtering and normalization.

[0009] By adopting the above technical solutions, the original data often contains noise, redundant information or inconsistent data points, which will affect the accuracy of data analysis and destruction. Through denoising and filtering processing, the noise and interference in the data can be effectively removed, and the purity and reliability of the data can be improved. Normalization processing can convert data of different dimensions and ranges to the same scale, which is convenient for subsequent processing and analysis. The denoising and filtering operations in the preprocessing process can reduce random fluctuations and outliers in the data, making the data more stable and continuous. This is particularly important for subsequent data analysis and destruction, because stable data can provide more accurate analysis results and destruction decisions. The preprocessed data is more standardized and standardized, which is conducive to the automation of subsequent data analysis and destruction processes. For example, normalization processing can simplify the complexity of the data analysis algorithm and improve the operating efficiency of the algorithm. At the same time, the completion of the preprocessing step also provides a more accurate and reliable data basis for the subsequent data destruction strategy formulation. In the process of data destruction, it is crucial to accurately identify sensitive data and periodic data. The preprocessing process makes data classification and identification more accurate and reliable by improving data quality. This helps ensure that sensitive data is properly encrypted and stored, while periodic data can be properly destroyed by modifying the data status to avoid accidental or missed deletion. Preprocessing, as an important part of data governance, helps to establish a standardized data processing process. By clarifying the standards and methods of preprocessing, it can ensure that data follows unified standards and specifications in all aspects such as acquisition, processing, analysis and destruction, thereby improving the transparency and controllability of data governance.

[0010] Optionally, analyzing the data to be processed to obtain analysis results specifically includes: performing keyword recognition on the data to be processed; if it is determined that the data to be processed contains personal privacy data and / or corporate confidential data, determining that the data to be processed is sensitive data.

[0011] By adopting the above technical solution, keyword recognition technology can accurately match specific words or phrases in the data to be processed, which are usually closely related to personal privacy or corporate confidential data. This method can quickly and accurately identify data containing sensitive information and reduce the possibility of misjudgment and omission. Compared with manual review of data one by one, keyword recognition technology can automatically process large amounts of data and significantly improve processing efficiency. This is particularly important for organizations that need to process massive amounts of data, and can save a lot of manpower and time costs. The leakage of sensitive data may have serious consequences for individuals and companies, including economic losses and reputation damage. Timely identification and processing of sensitive data through keyword recognition technology can effectively prevent the occurrence of data leakage incidents and enhance data protection capabilities. In many industries and regions, data protection regulations require companies and organizations to take reasonable measures to protect personal privacy and sensitive information. Identifying sensitive data through keyword recognition technology and taking corresponding processing measures can help companies and organizations meet these compliance requirements and avoid possible legal risks and fines. By identifying sensitive data, data can be further classified into sensitive data and non-sensitive data. This classification helps companies and organizations better manage data and formulate more refined data management and destruction strategies. At the same time, it is also conducive to improving the security and compliance of data use.

[0012] Optionally, analyzing the data to be processed to obtain an analysis result specifically also includes: performing a time series analysis on the data to be processed to obtain a first feature and a second feature; calculating a feature similarity between the first feature and the second feature; if it is determined that the feature similarity is greater than or equal to a preset threshold, determining that the data to be processed is periodic data.

[0013] By adopting the above technical solutions, time series analysis can deeply explore the laws and patterns of data changes over time. By calculating the feature similarity between the first feature and the second feature and comparing it with the preset threshold, data with periodic characteristics can be accurately identified. This method is more accurate and reliable than simple manual judgment or identification methods based on fixed periods. Time series analysis is an advanced data analysis method that relies on complex algorithms and models to extract useful information from data. By introducing time series analysis to identify periodic data, not only the automation of data processing is improved, but also the intelligence level of data processing is improved. This makes the data processing process more efficient, accurate and predictable. Periodic data usually has a specific life cycle and value change law. By accurately identifying periodic data, enterprises can formulate data management and destruction strategies more finely. For example, for periodic data that is about to reach the end of its life cycle, enterprises can take appropriate destruction measures to release storage resources; while for periodic data that still has value, it can be retained and continued to be used. Accurate identification of periodic data helps optimize the utilization of storage resources. For periodic data that no longer needs to be retained, enterprises can destroy it in time to release storage space; and for data that needs to be stored for a long time, a more economical and efficient storage solution can be adopted. This can reduce the storage costs of enterprises and improve resource utilization efficiency. Periodic data may contain sensitive information or corporate secrets. By accurately identifying and properly handling periodic data, enterprises can reduce the risk of data leakage and improve data security. For example, for periodic data containing sensitive information, enterprises can take measures such as encrypted storage or secure isolation to protect data from illegal access or leakage.

[0014] Optionally, if the analysis result indicates that the data to be processed is sensitive data, the data to be processed is destroyed by encrypted storage, specifically including: selecting a preset number of first-level security processing points from multiple first-level security processing points to obtain multiple first-level security processing points; receiving a user public key input by a user; encrypting the data to be processed using the user public key input by the user to obtain first encrypted data, and sending the first encrypted data to each of the first security processing points; obtaining a device identifier and a security processing point public key corresponding to a second security processing point, the second security processing point being any one of multiple second-level security processing points connected to the first security processing point; adding the device identifier corresponding to the second security processing point to the first encrypted data to obtain first processed data; encrypting the first processed data using the security processing point public key corresponding to the second security processing point to obtain second encrypted data, so as to destroy the data to be processed.

[0015] By adopting the above technical solution, sensitive data is initially encrypted using the user's public key, ensuring that the data is not stolen or tampered with by unauthorized third parties during transmission. At the same time, the encrypted data is sent to multiple preset first-level security processing points, further increasing the security of the data. Even if a certain security processing point is attacked, other security processing points still retain the encrypted data, reducing the risk of data leakage. The encrypted data is distributed to multiple first-level security processing points to achieve distributed storage of data. This storage method not only improves the reliability and availability of data, but also reduces the impact of single point failures on data security through redundant storage. Even if a certain security processing point fails, other security processing points can still provide services, ensuring the continuous security of data. The introduction of secondary security processing points and the use of public key encryption technology again during data transmission increase the difficulty for attackers to obtain sensitive data. Attackers not only need to crack the first layer of encryption, but also need to obtain the public key and device identification of the secondary security processing point to further access or tamper with the data. This multi-level encryption and distribution mechanism makes attackers face higher technical barriers and costs. Throughout the process, the introduction of user public keys gives users greater control over their own data. Users can choose whether to authorize an entity to access their sensitive data, and can revoke previous authorization by changing the public key. This mechanism helps protect users' privacy rights and interests and prevent unauthorized access and abuse.

[0016] Optionally, if the analysis result indicates that the data to be processed is periodic data, the data to be processed is destroyed by modifying the data status, specifically including: modifying the data status of the data to be processed to a preset field, and the preset field is used to indicate that the data to be processed has been deleted or is inaccessible.

[0017] By adopting the above technical solution, compared with physically deleting data or completely encrypting data, modifying the data state is a faster and resource-saving destruction method. It does not require the actual movement or processing of the data itself, but simply changes the access rights or tags of the data. This can quickly respond to changes in data management policies while reducing the occupation of storage and processing resources. The way of modifying the data state provides higher flexibility and reversibility for data destruction. In some cases, if it is later found that the data is still useful or needs to be restored, the data can be re-accessed by changing the data state. This reversibility is particularly important for periodic data, because periodic data may become useful again at some point in the future. By modifying the data state of periodic data to a preset field indicating that it has been deleted or is inaccessible, the risk of data leakage can be effectively reduced. Even if the data still physically exists on the storage medium, unauthorized access will be strictly restricted because its state has been modified. This helps protect the sensitive information and trade secrets of the enterprise.

[0018] Optionally, the method also includes: receiving a decryption request input by the user; sending a decryption instruction to the first security processing point according to the decryption request; controlling the first security processing point to decrypt the first encrypted data according to the decryption instruction using a security processing point private key corresponding to a security processing point public key corresponding to the first security processing point to obtain second processed data; controlling the first security processing point to extract an identifier from the second processed data to determine whether a device identifier corresponding to the first security processing point can be extracted; if it is determined that the device identifier corresponding to the first security processing point can be extracted, deleting the device identifier corresponding to the first security processing point from the first processed data to obtain the second encrypted data to access the data to be processed.

[0019] By adopting the above technical solution, the security of data access is increased by requiring the user to enter a decryption request and sending a decryption instruction after verification. This can prevent unauthorized access attempts and ensure that only legitimate users can access the encrypted data. Decrypting the first encrypted data using the private key of the security processing point corresponding to the first security processing point is a common security practice in encrypted communication and storage. The privacy and uniqueness of the private key ensure that only authorized parties can decrypt the data, further enhancing the security of the data. During the decryption process, the integrity of the data and the reliability of the source can be ensured by controlling the first security processing point to extract and verify the device identification of the decrypted data. If the device identification does not match or cannot be extracted, it may indicate that the data has been tampered with or forged during transmission or storage, thereby preventing further access to the data. Although the process is complicated, it ensures the security of the data and the legitimacy of user access. Once the user makes a decryption request through legal channels, they will be able to successfully access the required data. This combination of security and convenience improves the user experience. The extraction and verification process of the device identification not only enhances the security of the data, but also facilitates data tracking and auditing. If data leakage or improper access occurs, the flow and access of data can be traced by tracking the device identification, and then appropriate remedial measures can be taken. After extracting and verifying the device identification, the identification is deleted from the first processed data to obtain the second encrypted data. Although this step may seem small, it can significantly reduce data redundancy and storage space usage in large-scale data processing and storage scenarios, thereby improving storage and transmission efficiency.

[0020] In a second aspect of the present application, a data destruction device is provided, which includes an acquisition module and a processing module, wherein the acquisition module is used to acquire data to be processed; the processing module is used to analyze the data to be processed and obtain an analysis result; the processing module is also used to destroy the data to be processed by encrypted storage if the analysis result indicates that the data to be processed is sensitive data; the processing module is also used to destroy the data to be processed by modifying the data status if the analysis result indicates that the data to be processed is periodic data.

[0021] In the third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs the method described above.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, the method described above is executed.

[0023] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: For sensitive data, destroying it by encrypting and storing it actually converts it into a state that cannot be easily read or restored. This method effectively prevents the risk of illegal recovery and leakage of sensitive data after deletion, thereby improving data security. The encryption process ensures that even if the storage medium is lost or stolen, unauthorized third parties cannot obtain the original data content. This method automatically distinguishes between sensitive data and periodic data by intelligently analyzing the nature of the data to be processed, and adopts corresponding destruction strategies. This automated processing method reduces the need for manual intervention and improves the efficiency of data management. In particular, it can significantly reduce time and labor costs when processing large amounts of data. In many industries and regions, data protection regulations require companies and organizations to take reasonable measures to protect personal privacy and sensitive information. This method helps companies and organizations meet these compliance requirements and avoid possible legal risks and fines by encrypting and storing sensitive data and managing periodic data reasonably. For periodic data, destruction is carried out by modifying the data state instead of directly deleting it, retaining some traces or metadata of the data. The advantage of this is that data audits or historical analysis can be performed when necessary without worrying about the complete loss of data. Therefore, the above method facilitates the rationalization of data destruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flowchart of a data destruction method provided in an embodiment of the present application.

[0025] Figure 2 Another flowchart of a data destruction method provided in an embodiment of the present application.

[0026] Figure 3 A module schematic diagram of a data destruction device provided in an embodiment of the present application.

[0027] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0028] Explanation of the reference numerals: 31, acquisition module; 32, processing module; 41, processor; 42, communication bus; 43, user interface; 44, network interface; 45, memory. DETAILED DESCRIPTION

[0029] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0030] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0031] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0032] In today's vast field of data processing and storage, data destruction is increasingly important as a key link in maintaining the integrity of the data lifecycle, but it is often underestimated and ignored. At present, the practice of data destruction generally faces many challenges and unreasonable aspects, which not only pose a serious threat to personal privacy protection, but also have an adverse impact on the compliance, efficiency and security of enterprise data management.

[0033] Traditionally, data destruction methods are mostly limited to basic deletion operations, such as directly removing records from the database or clearing file contents. Although these methods are simple and easy to implement, they are difficult to effectively ensure the complete removal and security protection of sensitive data. More importantly, they ignore the compliance requirements and the potential for re-exploring data value during the data destruction process. They can neither meet the sophisticated needs of periodic data management nor promote the rational recycling of data resources, thus limiting the rationality and effectiveness of data destruction strategies.

[0034] In order to solve the above technical problems, this application provides a data destruction method, referring to Figure 1 , Figure 1 The following is a flow chart of a data destruction method provided in an embodiment of the present application. The data destruction method is applied to a server and includes steps S110 to S140, which are as follows: S110: Obtain data to be processed.

[0035] Specifically, a server refers to a computer program or device that provides services in a network environment, which responds to and processes requests from other devices (such as client computers, mobile phones, tablets, etc.). In an embodiment of the present application, the server generally obtains data by establishing a connection with a data source, executing a query or request, and then waiting for the data to be returned. Pending data refers to data that has been collected, generated, or stored somewhere, but has not yet been further processed or analyzed by a server program or application. These data may include user input, sensor data, log files, business transaction records, etc., which are essential for performing subsequent calculations, analysis, reporting, or storage operations.

[0036] In a possible implementation, obtaining the data to be processed specifically includes: obtaining original data; preprocessing the original data to obtain the data to be processed, wherein the preprocessing includes denoising, filtering, and normalization.

[0037] Specifically, obtaining raw data refers to obtaining unprocessed data directly from data sources (such as sensors, log files, databases, user input, etc.). These data may contain various noises, outliers, or inconsistent formats, and are not suitable for direct use in subsequent analysis or calculations. Preprocessing is a very critical step in data processing, which aims to improve the quality of data and make it more suitable for subsequent analysis tasks. The preprocessing process includes denoising, filtering, and normalization. Denoising is used to remove noise or random errors in data. Noise may come from a variety of factors, such as sensor inaccuracy, interference from the measurement environment, etc. There are many different methods for denoising, such as smoothing techniques, median filtering, wavelet transform, etc., depending on the characteristics of the data and the type of noise. Filtering is often related to denoising, but it focuses more on enhancing or weakening specific frequency components in the data through a certain algorithm or filter. For example, a low-pass filter can remove high-frequency noise, while a high-pass filter may be used to remove low-frequency trends or baseline drift. Normalization is to scale the data so that it falls into a small specific interval (usually [0,1] or [-1,1]). The purpose of this is to eliminate the impact of different dimensions on data analysis so that data from different sources or different ranges can be compared and analyzed on the same scale.

[0038] S120, analyzing the data to be processed to obtain analysis results.

[0039] Specifically, the data to be processed refers to the data that has been preprocessed (such as denoising, filtering, normalization, etc.), and its quality has been improved, making it more suitable for subsequent destruction tasks. These data may contain various types of information, such as numerical data, text data, time series data, etc.

[0040] In a possible implementation, the data to be processed is analyzed to obtain analysis results, which specifically include: performing keyword recognition on the data to be processed; if it is determined that the data to be processed contains personal privacy data and / or corporate confidential data, then determining that the data to be processed is sensitive data.

[0041] Specifically, keyword identification is a step in data analysis that uses pattern matching techniques such as predefined keyword lists or regular expressions to search for specific words, phrases or patterns in the data to be processed. These keywords are usually associated with the type of information that needs to be protected, such as personally identifiable information (PII), financial information, medical records, company secrets, etc. The purpose of keyword identification is to quickly screen out data fragments that may contain sensitive information for further review and processing. Personal privacy data refers to information that can identify or trace a specific individual, such as name, address, telephone number, email address, social security number, biometric information, etc. This information is protected by privacy protection laws and regulations and cannot be disclosed without authorization. Corporate confidential data refers to information that a company owns and wants to keep secret, such as trade secrets, technical information, customer lists, contract content, financial data, etc. This information is critical to the competitiveness and business operations of the company, and leakage may result in significant losses. If keywords related to personal privacy data or corporate confidential data are identified in the data to be processed, then the data is considered sensitive data. This identification process is crucial to protecting personal privacy, safeguarding corporate interests, and complying with relevant laws and regulations.

[0042] For example, suppose a financial services company is processing loan application data submitted by customers. This data contains the customer's personal information (such as name, ID number, proof of income, etc.) and the specific content of the loan application (such as loan amount, purpose, repayment period, etc.). The data to be processed is the loan application data submitted by the customer, including text, numbers and other forms of information. The company's server performs keyword recognition on the loan application data. The predefined keyword list may include words related to personal privacy such as "ID number", "bank card number", "home address", "annual income", and words related to corporate confidentiality such as "business plan", "competitor information", and "contract details". Through keyword recognition, the analysis tool found that some data fragments contain keywords such as "ID number" and "home address". Based on the results of keyword recognition, the company determined that these data fragments contain personal privacy data, so they were classified as sensitive data. In order to protect customer privacy, the company will encrypt these sensitive data and take additional security measures during data storage and transmission. At the same time, the company will ensure that only authorized personnel can access and process these sensitive data to prevent data leakage and abuse.

[0043] In a possible implementation, analyzing the data to be processed to obtain an analysis result specifically includes: performing a time series analysis on the data to be processed to obtain a first feature and a second feature; calculating a feature similarity between the first feature and the second feature; and if it is determined that the feature similarity is greater than or equal to a preset threshold, determining that the data to be processed is periodic data.

[0044] Specifically, time series analysis is a branch of statistics that focuses on analyzing and predicting data sequences that change over time. In this context, it is used to explore the changing patterns of the data to be processed over time. In time series analysis, a feature refers to a measure or indicator that can describe certain characteristics of a data sequence. The "first feature" and "second feature" mentioned here may refer to data features extracted from different angles or different time scales. For example, they can be the mean, standard deviation, autocorrelation coefficient, Fourier transform coefficient, etc. of the data, which can reflect the distribution, fluctuation or periodicity of the data in time. Feature similarity is a measure of the degree of similarity between two features. In time series analysis, calculating feature similarity can help determine whether certain parts of the data sequence have similar properties or patterns. This can be achieved by calculating the distance between two feature vectors (such as Euclidean distance, Manhattan distance, cosine similarity, etc.). If the calculated feature similarity is greater than or equal to the preset threshold, it can be considered that the data parts represented by these features have a high degree of similarity, thereby inferring the existence of a periodic pattern in the data sequence. Conversely, if the calculated feature similarity is less than the preset threshold, there is no periodic pattern in the data sequence. Periodic data refers to a data sequence whose data values ​​change periodically over time, such as seasonal sales data, day and night temperature changes, etc. In the embodiment of the present application, periodic data refers to data that has expired or is no longer needed.

[0045] S130: If the analysis result indicates that the data to be processed is sensitive data, the data to be processed is destroyed by encrypted storage.

[0046] Specifically, in the data processing flow, a series of analyses will be performed on the data to be processed, including but not limited to keyword recognition, time series analysis, pattern recognition, etc., to determine whether the data contains sensitive information. If the analysis results clearly indicate that the data to be processed contains personal privacy data, corporate confidential data or any other form of sensitive information, then these data need to be specially processed to protect their security. Encrypted storage is a common data protection method that converts sensitive data into a format that can only be interpreted by authorized users holding specific keys through encryption algorithms. In this process, the data itself is not deleted, but encrypted. This means that even if the data is obtained by unauthorized persons, they cannot directly read or use the data because there is no decryption key. In the embodiment of the present application, "destruction" does not mean the complete deletion or destruction of data. It actually means making the data or changing the state of the data through encryption so that the data becomes unavailable or cannot be accessed by unauthorized parties. The purpose of encrypted storage is not to completely delete the data, but to ensure the security of the data during storage and transmission to prevent data leakage or malicious use.

[0047] In a possible implementation, if the analysis result indicates that the data to be processed is sensitive data, the data to be processed is destroyed by means of encrypted storage, specifically including: selecting a preset number of first-level security processing points from multiple first-level security processing points to obtain multiple first-level security processing points; receiving a user public key input by a user; encrypting the data to be processed using the user public key input by the user to obtain first encrypted data, and sending the first encrypted data to each first security processing point; obtaining a device identifier and a security processing point public key corresponding to a second security processing point, the second security processing point being any one of multiple second-level security processing points connected to the first security processing point; adding the device identifier corresponding to the second security processing point to the first encrypted data to obtain first processed data; encrypting the first processed data using the security processing point public key corresponding to the second security processing point to obtain second encrypted data, so as to destroy the data to be processed.

[0048] Specifically, in this process, there is first a network consisting of multiple first-level security processing points. These first-level security processing points may be servers, data centers or other nodes with security processing capabilities. According to preset rules or policies, a certain number of points are selected from these first-level security processing points as the targets of subsequent operations (i.e., first security processing points). The user public key is a part of the key pair generated and made public by the user, which is used to encrypt data, and only the user holding the corresponding private key can decrypt it. In this step, the public key provided by the user is used to encrypt the data to be processed to generate the first encrypted data. This ensures that only the user himself (or the authorized party holding the private key) can decrypt and access the original data. The first encrypted data is then sent to all selected first security processing points. Each first security processing point may be connected to multiple second-level security processing points, which further enhance the decentralization and security of data processing. From the second-level security processing points connected to each first security processing point, one (or more, according to the specific policy) is selected as the second security processing point. The device identification of the selected second security processing point is added to the first encrypted data to generate the first processed data. This step is to clarify which specific second-level security processing point the data will be sent to in the subsequent encryption process. The first processed data is encrypted again using the public key of the security processing point corresponding to the second security processing point to generate the second encrypted data. This layer of encryption further enhances the security of the data because only the second security processing point holding the corresponding private key can decrypt the data. Finally, the second encrypted data is sent to the corresponding second security processing point for storage or further processing.

[0049] S140: If the analysis result indicates that the data to be processed is periodic data, the data to be processed is destroyed by modifying the data status.

[0050] Specifically, when the analysis results indicate that the data to be processed is periodic data, this usually means that the data follows a predictable pattern (such as seasonality, periodic fluctuations, etc.), and the data may become important or relevant again at some point in the future. Therefore, directly deleting these data may not be the best option, especially if they are valuable for future analysis, prediction or decision-making processes. In an embodiment of the present application, "destroying" periodic data by "modifying the data state" actually means removing the data from the current workflow or active data set and placing it in a safer and more manageable state, such as archive storage or cold storage. Doing so ensures that the data is not deleted immediately, but does not take up valuable resources when it is no longer needed for frequent access. In addition, modifying the data state may also include changing the access rights to the data, limiting access to the data to specific users or systems, thereby enhancing the security of the data.

[0051] In a possible implementation, if the analysis result indicates that the data to be processed is periodic data, the data to be processed is destroyed by modifying the data status, specifically including: modifying the data status of the data to be processed to a preset field, the preset field is used to indicate that the data to be processed has been deleted or is inaccessible.

[0052] Specifically, in a database, each data item usually has status information associated with it, which is used to describe the current status of the data, such as whether it is active, deleted, or needs further processing. When the analysis results indicate that the data to be processed is periodic data, the system will modify the data status of the data to a preset specific field value. This preset field is usually an identifier with a clear meaning, which is used to tell the system and other users that the data has been considered "deleted" or "inaccessible". The value of the preset field is predefined and represents a specific situation of the data status. In this scenario, the value of the preset field is used to indicate that the data is no longer part of the current active data set and may have been archived, deleted, or set to be visible only to specific users or systems. It is important that the value of this preset field should be able to clearly convey the current status of the data to avoid confusion or misunderstanding. For example, the preset field is "inaccessible state".

[0053] In one possible implementation, refer to Figure 2 , Figure 2Another flow chart of a data destruction method provided by an embodiment of the present application. It includes steps S210 to S250, and the above steps are as follows: S210, receiving a decryption request input by a user; S220, sending a decryption instruction to a first security processing point according to the decryption request; S230, controlling the first security processing point to decrypt the first encrypted data according to the decryption instruction using a security processing point private key corresponding to a security processing point public key corresponding to the first security processing point, to obtain second processed data; S240, controlling the first security processing point to extract an identifier from the second processed data, and determining whether a device identifier corresponding to the first security processing point can be extracted; S250, if it is determined that the device identifier corresponding to the first security processing point can be extracted, deleting the device identifier corresponding to the first security processing point from the first processed data, and obtaining second encrypted data to access the data to be processed.

[0054] Specifically, a user wants to access some encrypted data (data to be processed), so he / she initiates a decryption request to the server. This request may contain some basic information required for decryption, such as an identifier of the encrypted data or decryption authority verification. After receiving the decryption request, the server will send a decryption instruction to the designated secure processing point based on the information in the request. This instruction tells the secure processing point that the decryption operation needs to be performed and may contain specific parameters or data required for decryption. After receiving the decryption instruction, the first secure processing point will use the private key corresponding to its own public key to decrypt the encrypted data. This is a typical application of asymmetric encryption, where the public key is used to encrypt data and the corresponding private key is used to decrypt data. The data obtained after decryption is called "second processed data". After decryption, the first secure processing point will further process the second processed data and try to extract the device identifier from it. This device identifier is deliberately added when processing the data (perhaps before or during encryption) to identify the device or server that processes the data. If the device identifier corresponding to the first secure processing point can be successfully extracted from the data, it means that the data was generated by the secure processing point or a source it trusts, thereby verifying the legitimacy and source of the data.

[0055] Once the legitimacy of the data is verified, the first security processing point will delete its own device identification from the processed data (to avoid leakage in subsequent transmission) and obtain "second encrypted data" (although the name contains "encrypted", this refers to data that has been verified and decrypted, or data that may need to be encrypted again in subsequent processing). After that, the server can continue to perform other processing or access the second encrypted data as needed.

[0056] The present application also provides a data destruction device, referring to Figure 3 , Figure 3A schematic diagram of a module of a data destruction device provided in an embodiment of the present application. The data destruction device is a server, and the server includes an acquisition module 31 and a processing module 32, wherein the acquisition module 31 acquires the data to be processed; the processing module 32 analyzes the data to be processed and obtains an analysis result; if the analysis result of the processing module 32 indicates that the data to be processed is sensitive data, the data to be processed is destroyed by encrypted storage; if the analysis result of the processing module 32 indicates that the data to be processed is periodic data, the data to be processed is destroyed by modifying the data state.

[0057] In a possible implementation, the acquisition module 31 acquires the data to be processed, specifically including: the acquisition module 31 acquires original data; the processing module 32 preprocesses the original data to obtain the data to be processed, and the preprocessing includes denoising, filtering and normalization.

[0058] In a possible implementation, the processing module 32 analyzes the data to be processed and obtains an analysis result, which specifically includes: the processing module 32 performs keyword recognition on the data to be processed; if the processing module 32 determines that the data to be processed contains personal privacy data and / or corporate confidential data, then the processing module 32 determines that the data to be processed is sensitive data.

[0059] In a possible implementation, the processing module 32 analyzes the data to be processed to obtain an analysis result, which specifically includes: the processing module 32 performs a time series analysis on the data to be processed to obtain a first feature and a second feature; the processing module 32 calculates the feature similarity between the first feature and the second feature; if the processing module 32 determines that the feature similarity is greater than or equal to a preset threshold, it determines that the data to be processed is periodic data.

[0060] In a possible implementation, if the analysis result of the processing module 32 indicates that the data to be processed is sensitive data, the data to be processed is destroyed by encrypted storage, specifically including: the processing module 32 selects a preset number of first-level security processing points from multiple first-level security processing points to obtain multiple first-level security processing points; the acquisition module 31 receives a user public key input by a user; the processing module 32 uses the user public key input by the user to encrypt the data to be processed to obtain first encrypted data, and sends the first encrypted data to each first security processing point; the acquisition module 31 obtains the device identifier and the security processing point public key corresponding to the second security processing point, and the second security processing point is any one of the multiple second-level security processing points connected to the first security processing point; the processing module 32 adds the device identifier corresponding to the second security processing point to the first encrypted data to obtain the first processed data; the processing module 32 uses the security processing point public key corresponding to the second security processing point to encrypt the first processed data to obtain the second encrypted data, so as to destroy the data to be processed.

[0061] In a possible implementation, if the analysis result of the processing module 32 indicates that the data to be processed is periodic data, the data to be processed is destroyed by modifying the data status, specifically including: the processing module 32 modifies the data status of the data to be processed to a preset field, and the preset field is used to indicate that the data to be processed has been deleted or is inaccessible.

[0062] In a possible implementation, the acquisition module 31 receives a decryption request input by a user; the processing module 32 sends a decryption instruction to the first security processing point according to the decryption request; the processing module 32 controls the first security processing point to decrypt the first encrypted data according to the decryption instruction using the security processing point private key corresponding to the security processing point public key corresponding to the first security processing point to obtain second processed data; the processing module 32 controls the first security processing point to extract the identifier of the second processed data to determine whether the device identifier corresponding to the first security processing point can be extracted; if the processing module 32 determines that the device identifier corresponding to the first security processing point can be extracted, the device identifier corresponding to the first security processing point is deleted from the first processed data to obtain the second encrypted data for accessing the data to be processed.

[0063] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0064] The present application also provides an electronic device, referring to Figure 4 , Figure 4 The electronic device may include: at least one processor 41 , at least one network interface 44 , a user interface 43 , a memory 45 , and at least one communication bus 42 .

[0065] The communication bus 42 is used to realize the connection and communication between these components.

[0066] The user interface 43 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 43 may also include a standard wired interface and a wireless interface.

[0067] The network interface 44 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0068] Among them, the processor 41 may include one or more processing cores. The processor 41 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 45, and calling data stored in the memory 45. Optionally, the processor 41 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 41 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 41, and it can be implemented separately through a chip.

[0069] Among them, the memory 45 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 45 includes a non-transitory computer-readable storage medium. The memory 45 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 45 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 45 may also be optionally at least one storage device located away from the aforementioned processor 41. As Figure 4 As shown, the memory 45 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a data destruction method.

[0070] exist Figure 4In the electronic device shown, the user interface 43 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 41 can be used to call an application program storing a data destruction method in the memory 45, which, when executed by one or more processors, enables the electronic device to execute one or more methods in the above-mentioned embodiments.

[0071] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0072] The present application also provides a computer-readable storage medium, which stores instructions. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0073] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0074] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0075] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0076] In addition, each functional unit in each embodiment of the present application 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 software functional units.

[0077] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0078] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A data destruction method, characterized in that: The method comprises: Get the data to be processed; Analyzing the data to be processed to obtain analysis results; If the analysis result indicates that the data to be processed is sensitive data, the data to be processed is destroyed by encrypted storage; If the analysis result indicates that the data to be processed is periodic data, the data to be processed is destroyed by modifying the data state.

2. The data destruction method according to claim 1, characterized in that: The obtaining of the data to be processed specifically includes: Get the original data; The raw data is preprocessed to obtain the data to be processed, wherein the preprocessing includes denoising, filtering and normalization.

3. The data destruction method according to claim 1, characterized in that: The analyzing the data to be processed to obtain the analysis result specifically includes: Performing keyword recognition on the data to be processed; If it is determined that the data to be processed contains personal privacy data and / or corporate confidential data, then the data to be processed is determined to be sensitive data.

4. The data destruction method according to claim 3, characterized in that: The analyzing the data to be processed to obtain analysis results specifically includes: Performing time series analysis on the data to be processed to obtain a first feature and a second feature; Calculating feature similarity between the first feature and the second feature; If it is determined that the feature similarity is greater than or equal to a preset threshold, it is determined that the data to be processed is periodic data.

5. The data destruction method according to claim 1, characterized in that: If the analysis result indicates that the data to be processed is sensitive data, the data to be processed is destroyed by encrypted storage, specifically including: Selecting a preset number of first-level security processing points from connecting multiple first-level security processing points to obtain multiple first security processing points; Receive the user public key input by the user; Encrypting the data to be processed using the user public key input by the user to obtain first encrypted data, and sending the first encrypted data to each of the first security processing points; Obtaining a device identifier and a security processing point public key corresponding to a second security processing point, where the second security processing point is any one of a plurality of secondary security processing points connected to the first security processing point; adding a device identifier corresponding to the second secure processing point to the first encrypted data to obtain first processed data; The first processed data is encrypted using the security processing point public key corresponding to the second security processing point to obtain second encrypted data, so as to destroy the data to be processed.

6. The data destruction method according to claim 1, characterized in that: If the analysis result indicates that the data to be processed is periodic data, the data to be processed is destroyed by modifying the data state, specifically including: The data status of the data to be processed is modified to a preset field, where the preset field is used to indicate that the data to be processed has been deleted or is inaccessible.

7. The data destruction method according to claim 5, characterized in that: The method further comprises: receiving a decryption request input by the user; sending a decryption instruction to the first security processing point according to the decryption request; Control the first security processing point to decrypt the first encrypted data according to the decryption instruction using a security processing point private key corresponding to a security processing point public key corresponding to the first security processing point to obtain second processed data; Controlling the first security processing point to extract the identifier of the second processing data, and determining whether a device identifier corresponding to the first security processing point can be extracted; If it is determined that the device identification corresponding to the first security processing point can be extracted, the device identification corresponding to the first security processing point is deleted from the first processed data to obtain the second encrypted data to access the data to be processed.

8. A data destruction device, characterized in that: The data destruction device comprises an acquisition module (31) and a processing module (32), wherein: The acquisition module (31) is used to acquire data to be processed; The processing module (32) is used to analyze the data to be processed to obtain analysis results; The processing module (32) is further configured to destroy the data to be processed by means of encrypted storage if the analysis result indicates that the data to be processed is sensitive data; The processing module (32) is further configured to destroy the data to be processed by modifying the data state if the analysis result indicates that the data to be processed is periodic data.

9. An electronic device, characterized in that: The electronic device comprises a processor (41), a memory (45), a user interface (43) and a network interface (44), wherein the memory (45) is used to store instructions, the user interface (43) and the network interface (44) are both used to communicate with other devices, and the processor (41) is used to execute the instructions stored in the memory (45) so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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