Key storage method, electronic device, and storage medium

Abstract

The application discloses a key storage method, an electronic device and a storage medium. The method comprises the following steps: being applied to a data processing device, wherein a chip electric fuse is mounted in the data processing device, first, acquiring a root key stored in the chip electric fuse and service data corresponding to the data processing device, then, dividing the service data into n groups of target service data based on a preset division mode, then, determining n data sensitivity levels corresponding to the n groups of target service data, then, determining a hierarchical key corresponding to each group of target service data in the n groups of target service data based on the root key and the n data sensitivity levels, obtaining n hierarchical keys, and finally, storing the n hierarchical keys into a memory of the data processing device. The security of key storage is improved by adopting the application embodiment.

Description

Technical Field

[0001] This invention relates to the field of information security technology, and in particular to a key storage method, electronic device, and storage medium. Background Technology

[0002] With the widespread application of data processing equipment, the secure storage and encryption protection of internal business data has become a core aspect of ensuring stable equipment operation. Chip-based electric fuses, due to their characteristics of being unaffected by power loss, resistant to physical attacks, and difficult to illegally tamper with, are often used to store the root key of data processing equipment.

[0003] However, chip fuses inherently have limited storage space. Storing all business keys directly in the fuse not only fails to meet the needs of multi-level business key usage due to storage capacity limitations, but also leads to a high concentration of security risks due to centralized key storage. If the root key is leaked, the entire key system will collapse. Therefore, improving the security of key storage is an urgent problem to be solved. Summary of the Invention

[0004] This application provides a key storage method, electronic device, and storage medium, which improves the security of key storage.

[0005] In a first aspect, embodiments of this application provide a key storage method applied to a data processing device, wherein the data processing device is equipped with a chip fuse, the method comprising: Obtain the root key stored in the chip's electric fuse and the corresponding business data of the data processing device; The business data is divided into n groups of target business data based on a preset partitioning method; n is a positive integer. Determine n data sensitivity levels corresponding to the n sets of target business data; each target business data corresponds to one data sensitivity level; Based on the root key and the n data sensitivity levels, determine the hierarchical key corresponding to each group of target business data in the n groups of target business data, and obtain n hierarchical keys; The n-level keys are stored in the memory of the data processing device; The determination of the n data sensitivity levels corresponding to the n sets of target business data includes: Determine the data sensitivity value corresponding to each of the n sets of target business data to obtain n data sensitivity values; the larger the data sensitivity value corresponding to the target business data, the greater the sensitivity of the target business data. The n data sensitivity levels are determined based on the n data sensitivity values; Specifically, determining the data sensitivity value corresponding to each group of target business data in the n groups of target business data, resulting in n data sensitivity values, includes: Determine the data importance value corresponding to the first set of target business data; the first set of target business data is any one of the n sets of target business data. Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value; Obtain the data storage duration and data access frequency corresponding to the first set of target business data; Determine a first optimization factor corresponding to the data storage duration and a second optimization factor corresponding to the data retrieval frequency; The reference data sensitivity value is adjusted based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

[0006] Secondly, embodiments of this application provide a key storage device applied to a data processing device, wherein the data processing device is equipped with a chip fuse, and the device includes: an acquisition unit and a processing unit; The acquisition unit is used to acquire the root key stored in the chip fuse and the business data corresponding to the data processing device. The processing unit is used to divide the business data into n groups of target business data based on a preset division method; n is a positive integer; Determine n data sensitivity levels corresponding to the n sets of target business data; each target business data corresponds to one data sensitivity level; Based on the root key and the n data sensitivity levels, determine the hierarchical key corresponding to each group of target business data in the n groups of target business data, and obtain n hierarchical keys; The n-level keys are stored in the memory of the data processing device; The determination of the n data sensitivity levels corresponding to the n sets of target business data includes: Determine the data sensitivity value corresponding to each of the n sets of target business data to obtain n data sensitivity values; the larger the data sensitivity value corresponding to the target business data, the greater the sensitivity of the target business data. The n data sensitivity levels are determined based on the n data sensitivity values; Specifically, determining the data sensitivity value corresponding to each group of target business data in the n groups of target business data, resulting in n data sensitivity values, includes: Determine the data importance value corresponding to the first set of target business data; the first set of target business data is any one of the n sets of target business data. Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value; Obtain the data storage duration and data access frequency corresponding to the first set of target business data; Determine a first optimization factor corresponding to the data storage duration and a second optimization factor corresponding to the data retrieval frequency; The reference data sensitivity value is adjusted based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

[0007] Thirdly, embodiments of the present invention provide an electronic device, including: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor to cause the electronic device to perform the method as described in the first aspect.

[0008] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that is executed by a processor to implement the method as described in the first aspect.

[0009] Fifthly, embodiments of the present invention provide a computer program product including a non-transitory computer-readable storage medium storing a computer program, such that a computer performs the method as described in the first aspect.

[0010] Implementing the embodiments of the present invention has the following beneficial effects: As can be seen, the key storage method described in this embodiment of the invention is applied to a data processing device equipped with a chip fuse. First, the root key stored in the chip fuse and the corresponding business data of the data processing device are obtained. Then, the business data is divided into n groups of target business data based on a preset partitioning method. Next, the data sensitivity value corresponding to each of the n groups of target business data is determined, resulting in n data sensitivity values. Specifically, the data importance value corresponding to any one of the n groups of target business data can be determined first, and then a reference data sensitivity value corresponding to the data importance value can be determined. Next, the data duration and data retrieval frequency corresponding to the target business data are obtained, and the data duration corresponds to... The first optimization factor and the second optimization factor corresponding to the frequency of data access are used to determine the data sensitivity value of the reference data. Based on the first and second optimization factors, the data sensitivity value of the target business data is adjusted to obtain the data sensitivity value corresponding to the target business data. Following this method, the data sensitivity value corresponding to each group of target business data in the n groups of target business data can be determined, resulting in n data sensitivity values. Then, based on the n data sensitivity values, n data sensitivity levels corresponding to the n groups of target business data are determined. Finally, based on the root key and the n data sensitivity levels, the hierarchical key corresponding to each group of target business data in the n groups of target business data is determined, resulting in n hierarchical keys. Finally, the n hierarchical keys are stored in the memory of the data processing device, improving the security of key storage. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application or the background art will be described below.

[0012] Figure 1 This is a flowchart of a key storage method provided in an embodiment of this application; Figure 2 This is a flowchart provided in an embodiment of the present application for determining n data sensitivity levels; Figure 3 This is a flowchart of determining n data sensitivity values ​​provided in an embodiment of this application; Figure 4 This is a flowchart provided by an embodiment of the present application for determining the data importance value corresponding to the first group of target business data; Figure 5 This is a flowchart of determining n-level keys provided in an embodiment of this application; Figure 6 This is a flowchart of an embodiment of the present application for determining the hierarchical key corresponding to the first set of target service data; Figure 7 This is a schematic diagram of the structure of a key storage device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0013] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present application.

[0014] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0015] In this document, the term "implementation" means that a specific feature, structure, or characteristic described in connection with an implementation may be included in at least one implementation of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same implementation, nor is it a separate or alternative implementation mutually exclusive with other implementations. It will be explicitly and implicitly understood by those skilled in the art that the implementations described herein can be combined with other implementations.

[0016] Please see Figure 1 , Figure 1 This is a flowchart of a key storage method provided in an embodiment of this application. The key storage method is applied to a data processing device, which is equipped with a chip fuse. The method includes, but is not limited to, the following steps: S101: Obtain the root key stored in the chip fuse and the business data corresponding to the data processing device.

[0017] In this embodiment, the data processing device refers to a hardware terminal or embedded device with data storage, computation, business execution, and security encryption functions. Internally, it includes a main controller, a storage unit, an encryption computation unit, and a chip-based electric fuse hardware module. This data processing device can be used to execute various business logics, store business data, and encrypt and protect the data. It can achieve hardware-level secure storage of the root key based on the chip-based electric fuse, and supports hierarchical key derivation and layered storage according to the sensitivity of the business data. It is suitable for scenarios requiring high-level data security protection, such as industrial control, terminal security, embedded systems, and IoT devices, including but not limited to smart terminals, embedded chip devices, security encryption devices, industrial data processing devices, and electronic devices with hardware security capabilities.

[0018] The data processing device in this embodiment can be any electronic device or embedded device that integrates a main control chip, a security processing chip, or a programmable logic chip, and has a built-in fuse hardware storage unit. This type of data processing device possesses key generation, key derivation, data encryption / decryption, data storage, and hardware secure boot capabilities. It can utilize the chip's unique identifier as a key derivation interference factor and complete multi-level key hierarchical derivation and encrypted storage based on the root key. It is suitable for application scenarios with high requirements for data security, hardware anti-copying, and key leakage prevention. Specifically, the data processing device can be industrial control equipment, IoT smart terminals, embedded chip devices, data encryption storage devices, programmable logic hardware security platforms, terminal security encryption devices, vehicle-mounted security control units, trusted execution environment devices, high-speed solid-state storage control devices, server terminals with hardware security capabilities, and various chip-level devices and system-level devices that require a fixed root key and hierarchical key management.

[0019] In this embodiment, the chip fuse is a one-time programmable hardware storage unit integrated inside the data processing device chip. It is a natively secure storage medium for the chip. The chip fuse is formed into a fusible metal wire structure on a silicon wafer through chip manufacturing processes. It possesses hardware security characteristics such as one-time writing, no data loss upon power loss, resistance to physical disassembly and probe attacks, and difficulty in unauthorized reading or tampering. Once data is written, it cannot be modified or deleted, effectively preventing the root key from being stolen, replaced, or cracked. The chip fuse is only used to store the root key, which has the highest security level for the device, and does not directly store business keys or business data. It provides a hardware-level root key for the entire key system and is the core hardware support for ensuring key security.

[0020] It needs to be explained that the chip fuse is integrated into the main control chip or security chip inside the data processing equipment during the manufacturing process. It is integrated with the core circuit of the chip and packaged as an inherent hardware module of the data processing equipment chip. It is not carried out through external connection, plug-in, or independent assembly. It works in conjunction with the chip's computing and storage units inside the data processing equipment, providing only the root key to the data processing equipment with hardware-level secure storage capabilities. The root key stored in the chip fuse is the highest-security original key in the entire key system of the data processing equipment. It is written into the chip fuse once before the data processing equipment leaves the factory using a special programming tool. It is only used as the basic key source for deriving hierarchical keys and does not directly participate in the encryption and decryption of business data. It is not exposed or read in plaintext. It can achieve hardware-level secure storage by leveraging the immutable, indelible, and physical attack-resistant hardware characteristics of the chip fuse.

[0021] In this embodiment, the business data corresponding to the data processing device may include various related data generated and processed by the data processing device during operation, control, interaction, storage and management. Specifically, it may include the device's own operating parameters, system configuration information, hardware status data, user operation records, identity authentication information, communication interaction data, file storage data, application running data, business process related data, device control instruction data, log audit data, and sensitive business information that needs to be encrypted and protected.

[0022] S102: Divide the business data into n groups of target business data based on a preset division method.

[0023] In this embodiment, n is a positive integer. Various types of business data generated and processed by the data processing device can be uniformly classified and divided according to preset sensitivity levels, data types, usage scenarios, security requirements, and data importance, thereby dividing the business data into n groups of target business data.

[0024] The preset classification method can be a unified classification rule set in advance based on the business attributes, security specifications, and usage scenarios of the data processing equipment. This rule takes the risk level after data leakage, data confidentiality requirements, data usage scope, and business function type as the core classification basis. Combined with the equipment's own security policy and system configuration, various types of business data are distinguished from high to low sensitivity levels. At the same time, they are classified and organized according to dimensions such as business function, data purpose, access permissions, and transmission method. The standard is set before the equipment is running or before data processing. After the data is generated, the business data is directly grouped according to this fixed rule, so that multiple sets of mutually independent and clearly defined target business data can be obtained.

[0025] S103: Determine the n data sensitivity levels corresponding to the n sets of target business data.

[0026] In this implementation, each target business data corresponds to a data sensitivity level. First, a sensitivity value is assigned to each group of target business data. Then, the obtained sensitivity values ​​are compared with preset threshold values. The sensitivity values ​​are categorized according to their range: target business data with sensitivity values ​​in the lower range are classified as low-sensitivity, those in the middle range as medium-sensitivity, and those in the higher range as high-sensitivity. This process determines a unique and matching data sensitivity level for all groups of target business data.

[0027] S104: Based on the root key and the n data sensitivity levels, determine the hierarchical key corresponding to each group of target business data in the n groups of target business data, and obtain n hierarchical keys.

[0028] In this implementation, the root key can be used as the basic key source. Combined with the data sensitivity level corresponding to each group of target business data, a key derivation algorithm is used to perform step-by-step operations on the root key. Different derivation parameters and operation processes are used for different sensitivity levels to generate a unique matching hierarchical key for each group of target business data. The higher the sensitivity level, the higher the security strength of the generated hierarchical key and the more stringent the protection mechanism. Finally, multiple hierarchical keys corresponding to each group of target business data are obtained, so that data with different sensitivity levels are encrypted and protected using different levels of keys.

[0029] S105: Store the n level keys into the memory of the data processing device.

[0030] In this embodiment, the memory of the data processing device is a hardware storage component inside the device, independent of the chip fuse, used for the persistent storage of regular data and keys. It has sufficient storage space to stably store all levels of keys derived from the root key, as well as various types of business data generated during device operation. The memory supports fast reading and writing of key data and secure access. It can work in coordination with the chip fuse, and is only used to store level keys and business-related data. It does not participate in the hardware security hardening of the root key, thereby meeting the storage and use requirements of multi-level keys and a large amount of business data while ensuring the secure isolation of the key system.

[0031] In this embodiment, multiple generated hierarchical keys can be written one by one into the memory configured inside the data processing device, so that each hierarchical key is associated with the corresponding sensitive level of business data. The memory can provide a stable and persistent storage environment for the hierarchical keys, which can be securely read and called during device operation. At the same time, the hierarchical keys are protected from being illegally read, tampered with or deleted in the memory through encrypted storage, thereby realizing the secure storage and management of hierarchical keys.

[0032] As can be seen, the above method can fully utilize the hardware-level security features of the chip fuse, storing only the root key with the highest security level in the fuse. This avoids the limitation of limited fuse storage space and ensures the security of the key system from the source. At the same time, by grouping business data and classifying it into sensitivity levels, targeted hierarchical keys can be generated to protect different sensitive data with different keys. This effectively reduces the security risks brought about by centralized key storage and avoids the loss of control of the entire system data due to the leakage of a single key. Storing the hierarchical keys in the memory of the data processing device can not only meet the storage requirements of multi-level keys, but also achieve the isolation of the root key and hierarchical keys, improving the security, flexibility and scalability of the overall key management. It can also meet the data security protection requirements of different business scenarios without increasing hardware costs.

[0033] Please see Figure 2 , Figure 2 This application provides a flowchart for determining n data sensitivity levels, including but not limited to the following steps: S201: Determine the data sensitivity value corresponding to each group of target business data in the n groups of target business data, and obtain n data sensitivity values.

[0034] In this embodiment, based on the confidentiality requirements, leakage impact scope, access permission level, data importance, and security protection requirements of each group of target business data in the n groups of target business data, a comprehensive evaluation can be carried out through preset quantitative scoring rules. The corresponding data sensitivity value is calculated for each group of target business data, and finally, a one-to-one corresponding data sensitivity value is obtained for all groups of target business data, that is, n data sensitivity values.

[0035] S202: Determine the n data sensitivity levels based on the n data sensitivity values.

[0036] In this embodiment, since the first data sensitivity value is any one of the n data sensitivity values, the method for determining the data sensitivity level corresponding to the first data sensitivity value can be used as an example to illustrate the method for determining the n data sensitivity levels corresponding to the n data sensitivity values.

[0037] For example, when the first data sensitivity value is less than or equal to the first preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be low sensitivity level. Specifically, the first data sensitivity value is any one of the n data sensitivity values, and the first group of target business data is the target business data corresponding to the first data sensitivity value among the n groups of target business data.

[0038] The first preset data sensitivity value is a critical reference value that is pre-set by the data processing equipment before operation to classify data sensitivity levels. The first preset data sensitivity value is determined and fixed in advance by the data processing equipment according to business security policies, data importance standards and system protection requirements. It serves as the dividing line between low sensitivity level and medium sensitivity level and is used to distinguish low-sensitivity business data from other levels of data.

[0039] Low sensitivity level is the lowest level of security protection in the data sensitivity level. It corresponds to routine business data that will not cause security risks if leaked, has a very small impact, and does not require high-strength encryption protection. This type of data is usually publicly accessible information or basic operational data. It can meet the security requirements by using a matching low-level key and will not affect the overall key system of the device or business security.

[0040] The data sensitivity value corresponding to the first set of target business data is compared with the preset first data sensitivity value. When the data sensitivity value is less than or equal to the first preset data sensitivity value, the data sensitivity level corresponding to the first set of target business data can be determined to be low sensitivity level, thereby completing the sensitivity level classification of the target business data.

[0041] For example, when the first data sensitivity value is greater than the first preset data sensitivity value and less than or equal to the second preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be medium sensitivity. Specifically, The second preset data sensitivity value is a second critical reference value that is pre-set by the data processing equipment before operation to classify data sensitivity levels. The second preset data sensitivity value is determined and fixed in advance by the data processing equipment according to business security policies, data importance standards and protection requirements. It serves as the dividing line between medium sensitivity level and high sensitivity level and is used to distinguish medium sensitivity business data from other levels of data.

[0042] Medium sensitivity level is the level of security protection requirements in the data sensitivity level. It corresponds to routine business data that would have a certain security impact if leaked and needs to be protected by appropriate encryption. This type of data is usually non-core information such as equipment operation configuration and ordinary business records. It can meet the security requirements by using a matching medium-level key and will not have a serious impact on the overall key system of the equipment and the security of core business.

[0043] The data sensitivity value corresponding to the first set of target business data is compared with the preset first and second preset data sensitivity values. When the data sensitivity value is greater than the first preset data sensitivity value and less than or equal to the second preset data sensitivity value, the data sensitivity level corresponding to the first set of target business data can be determined to be medium sensitivity level, thereby completing the sensitivity level classification of the target business data.

[0044] For example, when the first data sensitivity value is greater than the second preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be a high sensitivity level. Specifically, the high sensitivity level is the highest level of security protection among the data sensitivity levels. It corresponds to core key data that would cause significant security risks and seriously affect the operation of the equipment and business security if leaked. This type of data is usually important information such as identity authentication information, core configuration parameters, and key business instructions. It needs to be protected with high-strength protection using matching high-level keys to ensure the security of the overall key system of the equipment and core business.

[0045] The data sensitivity value corresponding to the first set of target business data is compared with the pre-set second preset data sensitivity value. When the data sensitivity value is greater than the second preset data sensitivity value, the data sensitivity level corresponding to the first set of target business data can be determined to be high sensitivity level, thereby completing the sensitivity level classification of the target business data.

[0046] It should be explained that, in addition to low, medium, and high sensitivity levels, more detailed data sensitivity levels can be set based on the actual business scenarios of the data processing equipment, security management standards, and the severity of the damage caused by data breaches. For example, internal general levels can be set for internal public access only, relatively sensitive levels for information involving some core information but not meeting the highest protection requirements, core sensitive levels for access only by authorized personnel, and temporary sensitive levels for temporary interaction that expire after use. These additional sensitivity levels can further refine data classification, enabling business data with different security needs to be matched with more appropriate protection strengths, making key layering more precise, security control more flexible, and meeting the differentiated encrypted storage needs of more complex business scenarios.

[0047] As can be seen, by first determining the data sensitivity value corresponding to the target business data, and then determining the corresponding data sensitivity level based on the data sensitivity value, it is possible to distinguish the leakage risks of different business data, thereby achieving hierarchical encryption protection of business data and improving the security protection of business data.

[0048] Please see Figure 3 , Figure 3 This application provides a flowchart for determining n data sensitivity values, including but not limited to the following steps: S301: Determine the data importance value corresponding to the first group of target business data.

[0049] In this embodiment, since the first data sensitivity value is any one of the n data sensitivity values, and the first group of target business data is the target business data in the n groups of target business data that corresponds to the first data sensitivity value, the data sensitivity value corresponding to each group of target business data in the n groups of target business data can be determined according to the method for determining the data sensitivity value corresponding to the first group of target business data. In this embodiment, the method for determining the data sensitivity value corresponding to the first group of target business data is mainly used as an example to explain the determination of the data sensitivity value.

[0050] To determine the data sensitivity value corresponding to the first set of target business data, it is necessary to first determine the data importance value corresponding to the first set of target business data. This can be determined by combining parameters such as the number of related business modules, the time required for data recovery, the scale of economic losses caused by data leakage, the number of related users, the scope of data access permissions, whether the data involves compliance control content, the irreplaceability of the data, and the scope of business stagnation caused by the failure.

[0051] S302: Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value.

[0052] In this embodiment, it can be a preset mapping relationship between data importance value and data sensitivity value. Based on this mapping relationship, the data sensitivity value corresponding to the data importance value can be determined to obtain a reference data sensitivity value.

[0053] S303: Obtain the data storage duration and data call frequency corresponding to the first group of target business data.

[0054] In this embodiment, the data retention period is the complete retention cycle of the first set of target business data from the time it is generated until it is cleared and archived by the system. The data retention period can reflect the duration of data within the device's business operation cycle. The longer the retention period, the larger the exposure window for security threats such as theft and tampering, and the higher the corresponding data sensitivity.

[0055] Data access frequency refers to the total number of times the first set of target business data is accessed, read, and processed by various business modules within a fixed statistical period. The higher the access frequency of the first set of target business data, the stronger the dependence of multiple business processes on the data, the greater the negative impact on the business caused by data leakage or damage, and the higher the corresponding data sensitivity.

[0056] S304: Determine the first optimization factor corresponding to the data storage duration and the second optimization factor corresponding to the data retrieval frequency.

[0057] In this embodiment, it can be a first mapping relationship between a preset data duration and an optimization factor, and the first optimization factor corresponding to the data duration can be determined based on the first mapping relationship.

[0058] It can be a second mapping relationship between a preset data call frequency and an optimization factor, and based on this second mapping relationship, the second optimization factor corresponding to the data call frequency can be determined.

[0059] S305: Adjust the reference data sensitivity value based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

[0060] In this embodiment, the data sensitivity value corresponding to the first set of target business data can be calculated in the following manner: The data sensitivity value corresponding to the first set of target business data = reference data sensitivity value × (1 + first optimization factor) × (1 + second optimization factor); The reference data sensitivity value can be adjusted based on the first optimization factor and the second optimization factor in the manner described above to obtain the data sensitivity value corresponding to the first set of target business data.

[0061] It should be noted that the data sensitivity value corresponding to each group of target business data in the n groups of target business data can be determined in accordance with the method for determining the data sensitivity value corresponding to the first group of target business data described above, so as to obtain n data sensitivity values.

[0062] As can be seen, the reference data sensitivity value is first determined based on the data importance value of the first set of target business data. Then, the reference data sensitivity value is corrected by combining the two actual business attributes of the data storage duration and the data access frequency of the first set of target business data. The final data sensitivity value is determined by combining the data storage duration and the data access frequency of the first set of target business data. This makes the determined data sensitivity value closely match the actual security risk of the data and improves the accuracy of the sensitivity quantification results.

[0063] Please see Figure 4 , Figure 4 This application provides a flowchart for determining the data importance value corresponding to the first group of target business data, including but not limited to the following steps: S401: Determine the number of associated business modules corresponding to the first group of target business data and the time required for data recovery.

[0064] In this embodiment, the number of associated business modules corresponding to the first set of target business data is the total number of all business modules that rely on the first set of target business data to realize operation, data interaction and logical operation. The more associated business modules there are, the larger the range of business modules that will be affected and unable to operate normally after the first set of target business data is lost or leaked, the greater the overall negative impact of the data failure on the business, and the greater the data importance value corresponding to the first set of target business data.

[0065] The time required for data recovery corresponding to the first set of target business data is the length of time required to restore the incomplete data to a usable state after the first set of target business data has been damaged or lost. The longer the time required for data recovery, the longer the business stagnation period will be, and the corresponding economic losses and business interruption losses will increase accordingly. The greater the importance value of the data corresponding to the first set of target business data, the greater the importance value.

[0066] To avoid bias in assessing data importance based on a single factor and to ensure that the subsequent data importance values ​​align with the actual business value of the data, it is necessary to first determine the number of associated business modules corresponding to the first set of target business data and the time required for data recovery.

[0067] S402: Determine the first data importance value corresponding to the number of associated business modules and the second data importance value corresponding to the time required for data recovery.

[0068] In this embodiment, it can be a third mapping relationship between a preset number of associated business modules and a data importance value. Based on this third mapping relationship, the first data importance value corresponding to the number of associated business modules can be determined.

[0069] It can be a fourth mapping relationship between the preset data recovery time and the data importance value. Based on this fourth mapping relationship, the second data importance value corresponding to the data recovery time can be determined.

[0070] S403: Determine the data importance value corresponding to the first group of target business data based on the first data importance value and the second data importance value.

[0071] In this embodiment, for example, a reference data importance value is determined based on the first data importance value and the second data importance value. Specifically, a first weight corresponding to the first data importance value and a second weight corresponding to the second data importance value can be determined first, and then the first data importance value and the second data importance value can be merged by weighted summation to obtain the data importance value corresponding to the first set of target business data.

[0072] For example, the economic loss value corresponding to the damage of the first set of target business data is obtained. Specifically, the higher the economic loss value corresponding to the damage of the first set of target business data, the more serious the property loss and negative impact on operations caused by the failure of the data. This will increase the overall importance attribute of the data from an economic perspective, causing the data importance value to increase accordingly. The smaller the economic loss value, the lower the economic harm caused by the data damage, and the corresponding data importance value is also lower. Therefore, it is necessary to obtain the economic loss value corresponding to the damage of the first set of target business data first.

[0073] For example, the adjustment parameters corresponding to the economic loss value are determined. Specifically, this can be a preset mapping relationship between the economic loss value and the adjustment parameters, and the adjustment parameters corresponding to the economic loss value can be determined based on this mapping relationship.

[0074] For example, the importance value of the reference data is adjusted based on the adjustment parameters to obtain the data importance value corresponding to the first group of target business data. Specifically, the data importance value corresponding to the first group of target business data can be determined in the following manner: The data importance value corresponding to the first set of target business data = reference data importance value × (1 + adjustment parameter); The importance value of the reference data can be adjusted based on the adjustment parameters in the above manner to obtain the data importance value corresponding to the first set of target business data.

[0075] As can be seen, the importance values ​​of the first and second data are determined by the number of associated business modules and the time required for data recovery, respectively. The importance value of the reference data is then calculated by combining the importance values ​​of the first and second data. The economic loss value corresponding to the data damage is then introduced to generate adjustment parameters to correct the importance value of the reference data. The importance of the data is comprehensively calibrated from the dimensions of business impact scope, fault repair cost and economic loss, so that the final determined importance value of the data is consistent with the actual harm caused by the data damage.

[0076] Please see Figure 5 , Figure 5 This application provides a flowchart for determining n level keys, including but not limited to the following steps: S501: Determine the data sensitivity level corresponding to the first group of target business data among the n data sensitivity levels to obtain the first data sensitivity level.

[0077] In this embodiment, after determining the n data sensitivity levels corresponding to the n groups of target business data, the data sensitivity level corresponding to the first group of target business data can be selected from the n data sensitivity levels to obtain the first data sensitivity level.

[0078] It should be explained that, since the first set of target service data is any one of the n sets of target service data, the method for determining the hierarchical key corresponding to each set of target service data in the n sets of target service data is the same as the method for determining the hierarchical key corresponding to the first set of target service data. By determining the hierarchical key corresponding to the first set of target service data, the hierarchical key corresponding to each set of target service data in the n sets of target service data can be determined, thus obtaining n hierarchical keys.

[0079] S502: Determine the key-derived parameters corresponding to the first data sensitivity level.

[0080] In this embodiment, the key derivation parameters are pre-established with a one-to-one correspondence configuration relationship with each data sensitivity level. Different sensitivity levels are configured with different key derivation parameters. These key derivation parameters serve as constraint variables for deriving hierarchical keys based on the root key, and are used to limit the algorithm operation conditions in the key derivation process. By retrieving the matching key derivation parameters through the first data sensitivity level, the hierarchical keys generated based on the same root key can have a security protection strength adapted to the data sensitivity level, thereby realizing the generation of hierarchical keys with corresponding security specifications based on the data sensitivity level.

[0081] According to the preset hierarchical configuration rules, exclusive key derivative parameters can be set for different data sensitivity levels such as low sensitivity level, medium sensitivity level, and high sensitivity level. The value range and parameter type of each level parameter are defined in combination with the security design requirements of the encryption algorithm. After determining the first data sensitivity level, the key derivative parameters pre-bound for that level can be directly retrieved to complete the rapid matching and determination of derivative parameters.

[0082] Specifically, for low sensitivity levels, key derivative parameters with fewer encryption algorithm iterations and smaller key block bit lengths are pre-configured; for medium sensitivity levels, key derivative parameters with both encryption algorithm iterations and key block bit lengths at the middle standard are pre-configured; and for high sensitivity levels, key derivative parameters with more encryption algorithm iterations and larger key block bit lengths are pre-configured. After determining the first data sensitivity level corresponding to the first set of target business data, the key derivative parameters pre-bound for that sensitivity level are retrieved, and then the root key stored in the chip's electric fuse is substituted into the key derivative algorithm to complete the calculation. Finally, a hierarchical key with security protection strength matching the corresponding sensitivity level can be generated. The key derivation algorithm uses a pre-secured root key as the basic input source, and then incorporates key derivation parameters corresponding to the data sensitivity level as constraints. It completes multiple rounds of hash transformation and block iteration operations according to a predetermined cryptographic operation logic. By changing the configuration items such as the number of iteration operations and the key block bit length in the key derivation parameters, it can generate multiple layers of keys that are independent of each other and have different security strengths without changing the original root key content. The entire operation process follows standardized cryptographic specifications. It can not only rely on the same root key to achieve batch derivation of hierarchical keys, but also control the anti-cracking ability of each layer of keys through parameters, avoiding the security risk of all business data caused by the leakage of a single key.

[0083] S503: Determine the hierarchical key corresponding to the first group of target business data based on the key derivation parameters and the root key.

[0084] In this embodiment, the root key of unified storage management and the key derivative parameters matching the first data sensitivity level can be used together as the input data of the key derivative algorithm. The configuration information such as the number of algorithm iterations and the key block bit length contained in the key derivative parameters are brought into the operation rules of the key derivative algorithm. Continuous cryptographic calculation is carried out according to the preset hash iteration and block encryption operation steps. While keeping the root key unchanged, the operation process is changed by using differentiated derivative parameters. After the complete operation, the hierarchical key corresponding to the first group of target business data is obtained.

[0085] Based on the method for determining the hierarchical key corresponding to the first group of target business data, the hierarchical key corresponding to each group of target business data in the n groups of target business data can be determined, resulting in n hierarchical keys.

[0086] It should be explained that, in this embodiment, a unique fixed random salt value can be pre-configured for each data sensitivity level. After determining the first data sensitivity level, the salt value specific to that level is retrieved, and the salt value is concatenated with the original root key to form the original combined key. Then, a standard hash algorithm is used to perform a one-way hash operation on the concatenated data. Finally, the hash operation result is used as the hierarchical key corresponding to the first set of target business data. Different sensitivity levels can be paired with different salt values ​​to generate hierarchical keys that are non-repeating and have different levels of security strength, while keeping the root key unchanged.

[0087] Alternatively, the root key can be used as the top-level root node key of the key derivation tree. The branch levels of the key tree can be divided according to the data sensitivity level. The high sensitivity level corresponds to the multi-round derivation branch of the lower level of the key tree, and the low sensitivity level corresponds to the shallow derivation branch of the key tree. After determining the first data sensitivity level, the key tree is iteratively calculated from the upper level key downwards along the predetermined derivation path corresponding to that level to obtain the end node key. The end node key is then used as the level key for the corresponding business data. The key is derived in a hierarchical manner according to the sensitivity level by relying on the hierarchical division of the key tree.

[0088] It is also possible to pre-set a dedicated fixed numerical offset for each type of data sensitivity level. After determining the first data sensitivity level, the matching offset parameter is extracted, and the offset is XORed bit by bit with the complete root key. The result obtained after the operation is the level key corresponding to the first set of target business data. By changing the offset value corresponding to different sensitivity levels, various level keys with distinct security levels can be generated in batches based on the same root key.

[0089] Furthermore, the segmentation rules for the root key can be predefined according to different data sensitivity levels. After determining the first data sensitivity level, the corresponding field content is extracted from the complete root key data based on the start and end positions and the length of the extracted bytes corresponding to that level. The extracted key fields are directly used as the hierarchical key to adapt to the first set of target business data. The higher sensitivity level corresponds to the extraction of key segments with higher complexity and longer bit lengths from the root key, while the lower sensitivity level extracts key segments with fewer bit lengths. The segmentation extraction method enables the rapid generation of keys with different protection specifications and levels.

[0090] Please see Figure 6 , Figure 6 This application provides a flowchart for determining the hierarchical key corresponding to the first set of target service data, including but not limited to the following steps: S601: Determine the security encryption strength parameter corresponding to the first data sensitivity level.

[0091] In this embodiment, the security encryption strength parameters include the number of encryption rounds, algorithm complexity, and number of iterations. The number of encryption rounds represents the number of times the block encryption operation within the encryption algorithm is executed repeatedly. The algorithm complexity is determined by the key block length and the basic cryptographic operation paradigm. The number of iterations refers to the frequency of repeated operations in the hash compression transformation. Different first data sensitivity levels are pre-bound with different security encryption strength parameters. The higher the sensitivity level, the larger the configured values ​​for the number of encryption rounds, the block length corresponding to the algorithm, and the number of iterations.

[0092] According to the pre-defined hierarchical configuration specifications, the security encryption strength parameters such as the number of encryption rounds, algorithm complexity, and number of iterations can be configured differently based on the first data sensitivity level. The higher the sensitivity level, the more encryption rounds, the higher the algorithm complexity corresponding to the longer key blocks, and the larger the number of iterations. The lower the sensitivity level, the smaller the corresponding parameter configuration values ​​can be, thereby obtaining the security encryption strength parameters corresponding to the first data sensitivity level.

[0093] S602: Determine the operation rules based on the security encryption strength parameters.

[0094] In this implementation, the standard key-derived basic algorithm is customized according to the determined number of encryption rounds, algorithm complexity, and number of iterations. The segmentation method of group operation, the start and stop conditions of hash loop and data filling specifications are limited. The various security encryption strength parameters are implemented into executable cryptographic operation constraint logic, and exclusive operation rules adapted to the current sensitivity level are generated.

[0095] The operational rules are a complete execution logic customized on the basis of the standard key derivation algorithm framework, with the selected number of encryption rounds, algorithm complexity, and number of iterations as constraints. The number of encryption rounds determines the number of execution passes of block cipher cyclic encryption, the key block bit length, data padding format, and basic cryptographic operation type are determined according to the algorithm complexity, and the number of iterations limits the frequency of repeated execution of hash compression operations. The constraints corresponding to parameters such as the number of encryption rounds, algorithm complexity, and number of iterations are integrated into ordered operation steps, and the data concatenation order, input format, and data flow method of each stage of the root key and key derivation parameters are clearly defined, forming a standardized execution procedure that can be directly used for key calculation.

[0096] It should be explained that, in addition to the number of encryption rounds, algorithm complexity, and number of iterations, the operation rules can also include configuration parameters such as data padding method, initial vector value, data segment length, verification field generation rules, byte order arrangement specifications, and intermediate value caching strategy. Among them, the data padding method specifies the padding characters and padding logic when the key input data length is less than the standard block length; the initial vector is used to configure the initial random variable for the first round of block encryption operation; the data segment length defines the granularity of the segmentation when the root key and key-derived parameters participate in the operation; the verification field generation rules clarify the generation algorithm and attachment position of the integrity check code during the operation; the byte order arrangement specifications limit the arrangement of the high and low bits of binary data; and the intermediate value caching strategy constrains the temporary storage and retrieval method of intermediate results in each round of operation.

[0097] S603: Perform operations on the key derivative parameters and the root key based on the operation rules to obtain the hierarchical key corresponding to the first set of target business data.

[0098] In this embodiment, the root key and the key-derived parameters corresponding to the sensitivity level are used as input for the operation. The cryptographic operations such as block encryption and multiple rounds of hash iteration are carried out in strict accordance with the corresponding operation rules. After the complete process calculation, the hierarchical key that meets the protection requirements of the first group of target business data is obtained.

[0099] The hierarchical key corresponding to the first set of target business data is used for the encryption storage and decryption retrieval operations of the first set of target business data. During the business data storage stage, the hierarchical key is used to perform encryption operations on the business data according to the predetermined encryption algorithm and store the ciphertext. When the data needs to be retrieved and used later, the same hierarchical key is used to decrypt the ciphertext data to restore the original data. At the same time, the hierarchical key is bound to the corresponding business data and stored in isolation. Business data of different sensitivity levels do not use hierarchical keys. Even if a single hierarchical key is leaked, it will only threaten the data of the corresponding group and will not affect other business data and root keys derived from the same root key.

[0100] As can be seen, by determining the corresponding operation rules based on the security encryption strength parameters such as the number of encryption rounds, algorithm complexity, and number of iterations corresponding to the data sensitivity level, and then combining the key derivation parameters with the root key to generate hierarchical keys, the encryption strength of key generation can be flexibly adjusted according to the actual security needs of business data. High-sensitivity data is paired with higher security level parameters to generate high-security hierarchical keys, while low-sensitivity data is paired with lower security level parameters to generate low-cost hierarchical keys. Moreover, all hierarchical keys are derived hierarchically from a unified root key. Even if a single hierarchical key is leaked, it will not affect the root key and other block keys, thereby significantly improving the security of the entire key system.

[0101] In summary, implementing the embodiments of the present invention has the following beneficial effects: As can be seen, the key storage method described in this embodiment of the invention is applied to a data processing device equipped with a chip fuse. First, the root key stored in the chip fuse and the corresponding business data of the data processing device are obtained. Then, the business data is divided into n groups of target business data based on a preset partitioning method. Next, the data sensitivity value corresponding to each of the n groups of target business data is determined, resulting in n data sensitivity values. Specifically, the data importance value corresponding to any one of the n groups of target business data can be determined first, and then a reference data sensitivity value corresponding to the data importance value can be determined. Next, the data duration and data retrieval frequency corresponding to the target business data are obtained, and the data duration corresponds to... The first optimization factor and the second optimization factor corresponding to the frequency of data access are used to determine the data sensitivity value of the reference data. Based on the first and second optimization factors, the data sensitivity value of the target business data is adjusted to obtain the data sensitivity value corresponding to the target business data. Following this method, the data sensitivity value corresponding to each group of target business data in the n groups of target business data can be determined, resulting in n data sensitivity values. Then, based on the n data sensitivity values, n data sensitivity levels corresponding to the n groups of target business data are determined. Finally, based on the root key and the n data sensitivity levels, the hierarchical key corresponding to each group of target business data in the n groups of target business data is determined, resulting in n hierarchical keys. Finally, the n hierarchical keys are stored in the memory of the data processing device, improving the security of key storage.

[0102] Please see Figure 7 , Figure 7 This is a schematic diagram of a key storage device provided in an embodiment of the present application. The key storage device 700 is applied to a data processing device, which is equipped with a chip fuse. The key storage device 700 includes: an acquisition unit 701 and a processing unit 702. The acquisition unit 701 is used to acquire the root key stored in the chip fuse and the business data corresponding to the data processing device; The processing unit 702 is used to divide the business data into n groups of target business data based on a preset division method; n is a positive integer. Determine n data sensitivity levels corresponding to the n sets of target business data; each target business data corresponds to one data sensitivity level; Based on the root key and the n data sensitivity levels, determine the hierarchical key corresponding to each group of target business data in the n groups of target business data, and obtain n hierarchical keys; The n-level keys are stored in the memory of the data processing device; The determination of the n data sensitivity levels corresponding to the n sets of target business data includes: Determine the data sensitivity value corresponding to each of the n sets of target business data to obtain n data sensitivity values; the larger the data sensitivity value corresponding to the target business data, the greater the sensitivity of the target business data. The n data sensitivity levels are determined based on the n data sensitivity values; Specifically, determining the data sensitivity value corresponding to each group of target business data in the n groups of target business data, resulting in n data sensitivity values, includes: Determine the data importance value corresponding to the first set of target business data; the first set of target business data is any one of the n sets of target business data. Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value; Obtain the data storage duration and data access frequency corresponding to the first set of target business data; Determine a first optimization factor corresponding to the data storage duration and a second optimization factor corresponding to the data retrieval frequency; The reference data sensitivity value is adjusted based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

[0103] In some possible implementations, in determining the n data sensitivity levels based on the n data sensitivity values, the processing unit 702 is specifically configured to: When the first data sensitivity value is less than or equal to the first preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be low sensitivity level; the first data sensitivity value is the data sensitivity value corresponding to the first group of target business data among the n data sensitivity values. When the first data sensitivity value is greater than the first preset data sensitivity value and less than or equal to the second preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be medium sensitivity level; When the first data sensitivity value is greater than the second preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be a high sensitivity level.

[0104] In some possible implementations, in determining the data sensitivity value corresponding to each of the n sets of target business data to obtain n data sensitivity values, the processing unit 702 is specifically used for: Determine the data importance value corresponding to the first set of target business data; Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value; Obtain the data storage duration and data access frequency corresponding to the first set of target business data; Determine a first optimization factor corresponding to the data storage duration and a second optimization factor corresponding to the data retrieval frequency; The reference data sensitivity value is adjusted based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

[0105] In some possible implementations, the processing unit 702 is specifically used for determining the data importance value corresponding to the first set of target business data as follows: Determine the number of associated business modules corresponding to the first set of target business data and the time required for data recovery; Determine the first data importance value corresponding to the number of associated business modules and the second data importance value corresponding to the time required for data recovery; The data importance value corresponding to the first group of target business data is determined based on the first data importance value and the second data importance value.

[0106] In some possible implementations, in determining the data importance value corresponding to the first group of target business data based on the first data importance value and the second data importance value, the processing unit 702 is specifically used for: The importance value of reference data is determined based on the importance value of the first data and the importance value of the second data; Obtain the economic loss value corresponding to the damage to the first set of target business data; Determine the adjustment parameters corresponding to the economic loss value; Based on the adjustment parameters, the importance value of the reference data is adjusted to obtain the data importance value corresponding to the first set of target business data.

[0107] In some possible implementations, in determining the hierarchical key corresponding to each group of target service data in the n groups of target service data based on the root key and the n data sensitivity levels, to obtain n hierarchical keys, the processing unit 702 is specifically used for: Determine the data sensitivity level corresponding to the first group of target business data among the n data sensitivity levels to obtain the first data sensitivity level; Determine the key-derived parameters corresponding to the first data sensitivity level; The hierarchical key corresponding to the first set of target business data is determined based on the key derivation parameters and the root key.

[0108] In some possible implementations, in determining the hierarchical key corresponding to the first set of target service data based on the key derivation parameters and the root key, the processing unit 702 is specifically used for: Determine the security encryption strength parameter corresponding to the first data sensitivity level; the security encryption strength parameter includes the number of encryption rounds, algorithm complexity, and number of iterations; The operation rules are determined based on the aforementioned security encryption strength parameters; Based on the operation rules, the key derivative parameters and the root key are operated on to obtain the hierarchical key corresponding to the first set of target business data.

[0109] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 800 is applied to a data processing device, which includes a chip fuse. The electronic device 800 includes a transceiver 801, a processor 802, and a memory 803. They are connected via a bus 804. The memory 803 stores computer programs and data, and the transceiver 801 can transmit the data stored in the memory 803 to the processor 802. The program includes instructions for performing the following steps: Obtain the root key stored in the chip's electric fuse and the corresponding business data of the data processing device; The business data is divided into n groups of target business data based on a preset partitioning method; n is a positive integer. Determine n data sensitivity levels corresponding to the n sets of target business data; each target business data corresponds to one data sensitivity level; Based on the root key and the n data sensitivity levels, determine the hierarchical key corresponding to each group of target business data in the n groups of target business data, and obtain n hierarchical keys; The n-level keys are stored in the memory of the data processing device; The determination of the n data sensitivity levels corresponding to the n sets of target business data includes: Determine the data sensitivity value corresponding to each of the n sets of target business data to obtain n data sensitivity values; the larger the data sensitivity value corresponding to the target business data, the greater the sensitivity of the target business data. The n data sensitivity levels are determined based on the n data sensitivity values; Specifically, determining the data sensitivity value corresponding to each group of target business data in the n groups of target business data, resulting in n data sensitivity values, includes: Determine the data importance value corresponding to the first set of target business data; the first set of target business data is any one of the n sets of target business data. Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value; Obtain the data storage duration and data access frequency corresponding to the first set of target business data; Determine a first optimization factor corresponding to the data storage duration and a second optimization factor corresponding to the data retrieval frequency; The reference data sensitivity value is adjusted based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

[0110] In some possible implementations, in determining the n data sensitivity levels based on the n data sensitivity values, the above procedure includes instructions for performing the following steps: When the first data sensitivity value is less than or equal to the first preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be low sensitivity level; the first data sensitivity value is the data sensitivity value corresponding to the first group of target business data among the n data sensitivity values. When the first data sensitivity value is greater than the first preset data sensitivity value and less than or equal to the second preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be medium sensitivity level; When the first data sensitivity value is greater than the second preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be a high sensitivity level.

[0111] In some possible implementations, in determining the data sensitivity value corresponding to each of the n sets of target business data to obtain n data sensitivity values, the above procedure includes instructions for performing the following steps: Determine the data importance value corresponding to the first set of target business data; Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value; Obtain the data storage duration and data access frequency corresponding to the first set of target business data; Determine a first optimization factor corresponding to the data storage duration and a second optimization factor corresponding to the data retrieval frequency; The reference data sensitivity value is adjusted based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

[0112] In some possible implementations, the above procedure includes instructions for performing the following steps in determining the data importance value corresponding to the first set of target business data: Determine the number of associated business modules corresponding to the first set of target business data and the time required for data recovery; Determine the first data importance value corresponding to the number of associated business modules and the second data importance value corresponding to the time required for data recovery; The data importance value corresponding to the first group of target business data is determined based on the first data importance value and the second data importance value.

[0113] In some possible implementations, in determining the data importance value corresponding to the first set of target business data based on the first data importance value and the second data importance value, the above procedure includes instructions for performing the following steps: The importance value of reference data is determined based on the importance value of the first data and the importance value of the second data; Obtain the economic loss value corresponding to the damage to the first set of target business data; Determine the adjustment parameters corresponding to the economic loss value; Based on the adjustment parameters, the importance value of the reference data is adjusted to obtain the data importance value corresponding to the first set of target business data.

[0114] In some possible implementations, in determining the hierarchical key corresponding to each group of target service data in the n groups of target service data based on the root key and the n data sensitivity levels, to obtain n hierarchical keys, the above procedure includes instructions for performing the following steps: Determine the data sensitivity level corresponding to the first group of target business data among the n data sensitivity levels to obtain the first data sensitivity level; Determine the key-derived parameters corresponding to the first data sensitivity level; The hierarchical key corresponding to the first set of target business data is determined based on the key derivation parameters and the root key.

[0115] In some possible implementations, the above procedure includes instructions for performing the following steps in determining the hierarchical key corresponding to the first set of target service data based on the key derivation parameters and the root key: Determine the security encryption strength parameter corresponding to the first data sensitivity level; the security encryption strength parameter includes the number of encryption rounds, algorithm complexity, and number of iterations; The operation rules are determined based on the aforementioned security encryption strength parameters; Based on the operation rules, the key derivative parameters and the root key are operated on to obtain the hierarchical key corresponding to the first set of target business data.

[0116] It should be understood that the electronic devices in this application may include data processing devices, smartphones (such as Android phones, iOS phones, Windows Phones, etc.), tablet computers, PDAs, laptops, mobile internet devices (MIDs) or wearable devices, servers, edge computing nodes, etc. The above-mentioned electronic devices are merely examples and not exhaustive, and include, but are not limited to, the electronic devices described above.

[0117] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement some or all of the steps of any of the methods described in the above method embodiments.

[0118] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0119] It should be noted that, for the sake of simplicity, the aforementioned methods are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are optional, and the actions and modules involved are not necessarily essential to this application.

[0120] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0121] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0122] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0123] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.

[0124] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, 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. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0125] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0126] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The above description of the embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A key storage method, characterized in that, Applied to a data processing device, the data processing device being equipped with a chip fuse, the method includes: Obtain the root key stored in the chip's electric fuse and the corresponding business data of the data processing device; The business data is divided into n groups of target business data based on a preset partitioning method; n is a positive integer. Determine n data sensitivity levels corresponding to the n sets of target business data; each target business data corresponds to one data sensitivity level; Based on the root key and the n data sensitivity levels, determine the hierarchical key corresponding to each group of target business data in the n groups of target business data, and obtain n hierarchical keys; The n-level keys are stored in the memory of the data processing device; The determination of the n data sensitivity levels corresponding to the n sets of target business data includes: Determine the data sensitivity value corresponding to each of the n sets of target business data to obtain n data sensitivity values; the larger the data sensitivity value corresponding to the target business data, the greater the sensitivity of the target business data. The n data sensitivity levels are determined based on the n data sensitivity values; Specifically, determining the data sensitivity value corresponding to each group of target business data in the n groups of target business data, resulting in n data sensitivity values, includes: Determine the data importance value corresponding to the first group of target business data; the first group of target business data is any one of the n groups of target business data. Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value; Obtain the data storage duration and data access frequency corresponding to the first set of target business data; Determine a first optimization factor corresponding to the data storage duration and a second optimization factor corresponding to the data retrieval frequency; The reference data sensitivity value is adjusted based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

2. The method as described in claim 1, characterized in that, The process of determining the n data sensitivity levels based on the n data sensitivity values ​​includes: When the first data sensitivity value is less than or equal to the first preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be low sensitivity level; the first data sensitivity value is the data sensitivity value corresponding to the first group of target business data among the n data sensitivity values; When the first data sensitivity value is greater than the first preset data sensitivity value and less than or equal to the second preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be medium sensitivity level. When the first data sensitivity value is greater than the second preset data sensitivity value, the data sensitivity level corresponding to the first group of target business data is determined to be a high sensitivity level.

3. The method as described in claim 2, characterized in that, Determining the data importance value corresponding to the first group of target business data includes: Determine the number of associated business modules corresponding to the first set of target business data and the time required for data recovery; Determine the first data importance value corresponding to the number of associated business modules and the second data importance value corresponding to the time required for data recovery; The data importance value corresponding to the first group of target business data is determined based on the first data importance value and the second data importance value.

4. The method as described in claim 3, characterized in that, The step of determining the data importance value corresponding to the first group of target business data based on the first data importance value and the second data importance value includes: The importance value of reference data is determined based on the importance value of the first data and the importance value of the second data; Obtain the economic loss value corresponding to the damage to the first set of target business data; Determine the adjustment parameters corresponding to the economic loss value; Based on the adjustment parameters, the importance value of the reference data is adjusted to obtain the data importance value corresponding to the first set of target business data.

5. The method as described in claim 4, characterized in that, The process involves determining the hierarchical key corresponding to each group of target service data in the n groups of target service data based on the root key and the n data sensitivity levels, resulting in n hierarchical keys, including: Determine the data sensitivity level corresponding to the first group of target business data among the n data sensitivity levels to obtain the first data sensitivity level; Determine the key-derived parameters corresponding to the first data sensitivity level; The hierarchical key corresponding to the first set of target business data is determined based on the key derivation parameters and the root key.

6. The method as described in claim 5, characterized in that, The step of determining the hierarchical key corresponding to the first group of target service data based on the key derivation parameters and the root key includes: Determine the security encryption strength parameter corresponding to the first data sensitivity level; the security encryption strength parameter includes the number of encryption rounds, algorithm complexity, and number of iterations; The operation rules are determined based on the aforementioned security encryption strength parameters; Based on the operation rules, the key derivative parameters and the root key are operated on to obtain the hierarchical key corresponding to the first set of target business data.

7. A key storage device, characterized in that, A device for use in a data processing equipment, wherein the data processing equipment is equipped with a chip fuse, the device comprising: an acquisition unit and a processing unit; The acquisition unit is used to acquire the root key stored in the chip fuse and the business data corresponding to the data processing device; The processing unit is used to divide the business data into n groups of target business data based on a preset division method; n is a positive integer; Determine n data sensitivity levels corresponding to the n sets of target business data; each target business data corresponds to one data sensitivity level; Based on the root key and the n data sensitivity levels, determine the hierarchical key corresponding to each group of target business data in the n groups of target business data, and obtain n hierarchical keys; The n-level keys are stored in the memory of the data processing device; The determination of the n data sensitivity levels corresponding to the n sets of target business data includes: Determine the data sensitivity value corresponding to each of the n sets of target business data to obtain n data sensitivity values; the larger the data sensitivity value corresponding to the target business data, the greater the sensitivity of the target business data. The n data sensitivity levels are determined based on the n data sensitivity values; Specifically, determining the data sensitivity value corresponding to each group of target business data in the n groups of target business data, resulting in n data sensitivity values, includes: Determine the data importance value corresponding to the first group of target business data; the first group of target business data is any one of the n groups of target business data. Determine the data sensitivity value corresponding to the data importance value to obtain a reference data sensitivity value; Obtain the data storage duration and data access frequency corresponding to the first set of target business data; Determine a first optimization factor corresponding to the data storage duration and a second optimization factor corresponding to the data retrieval frequency; The reference data sensitivity value is adjusted based on the first optimization factor and the second optimization factor to obtain the data sensitivity value corresponding to the first set of target business data.

8. An electronic device, characterized in that, The method includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the one or more programs include instructions for performing the steps of the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the method as described in any one of claims 1-6.

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