Privacy protection method based on data on intelligent door lock chain

Abstract

The invention discloses a privacy protection method based on data on an intelligent door lock chain, and the method comprises the steps: setting a sensitivity coefficient according to the type of intelligent door lock data; setting a scene coefficient according to the use scene of the intelligent door lock; setting a threat coefficient according to a novel calculation attack sign of the intelligent door lock data; according to participants of data interaction of the intelligent door lock, an authority level is allocated to each participant; determining an encryption strength coefficient, and determining an encryption parameter according to the encryption strength coefficient and the sensitivity coefficient; determining a key according to the encryption parameter, encrypting the intelligent door lock data, and storing the encrypted intelligent door lock data in a block chain; when a participant needs to access the encrypted data on the intelligent door lock chain, authority verification is carried out on the authority level of the participant, and the participant passing the verification decrypts the encrypted data on the intelligent door lock chain by using a private key and a secret key and accesses the encrypted data on the intelligent door lock chain; and constructing a scoring function for data privacy protection on the intelligent door lock chain, and dynamically adjusting the encryption strength coefficient, the encryption parameter and the access authority according to the scoring function.

Description

Technical Field

[0001] This invention relates to the field of data security technology, and more specifically, to a privacy protection method based on data on a smart door lock chain. Background Technology

[0002] In the field of smart locks, the application of blockchain technology has brought new possibilities to data management due to its decentralized and immutable characteristics. However, with the development of new technologies such as quantum computing, traditional encryption algorithms face the risk of being cracked. Once the encryption algorithm is compromised, core data such as user authentication information and keys stored on the smart lock blockchain will be completely exposed, directly threatening users' property and personal safety.

[0003] Existing smart lock privacy protection methods have the following obvious shortcomings: (1) Data on the smart door lock chain has the characteristic of high-frequency update. Traditional homomorphic encryption, zero-knowledge proof and other privacy protection algorithms cannot achieve real-time encryption strategy iteration, which leads to the risk of long-term stored data being reverse-engineered. (2) Existing smart door locks mostly use fixed encryption modes for data privacy protection. They cannot dynamically adjust encryption parameters according to the data sensitivity level and usage scenario, resulting in over-encryption in low-risk scenarios, causing door lock response delay, while insufficient encryption in high-risk scenarios, leading to data leakage. (3) Smart door locks involve data interaction between multiple parties. Existing smart door lock data privacy protection methods lack a multi-party collaborative privacy protection mechanism. The data permissions of different participants are not deeply bound to the encryption algorithm, resulting in a lack of encryption-level defenses when permissions are abused. For example, when an administrator accesses user data without authorization, the existing encryption algorithm cannot provide effective protection. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a privacy protection method based on data on a smart door lock chain, in order to solve the problems of insufficient timeliness, poor dynamic adaptability, and weak collaborative protection capabilities in the existing data privacy protection of smart door lock chains.

[0005] To achieve the above technical objectives, the present invention adopts the following technical solution: A privacy protection method based on data on a smart door lock chain, the specific process of which is as follows: Collect smart lock data and set sensitivity coefficients based on the type of smart lock data; Set scenario coefficients based on the usage scenarios of smart door locks; Threat levels are set based on new computational attack patterns in smart lock data; Assign permission levels to each participant in the smart lock data interaction process. The encryption strength coefficient is determined based on the sensitivity coefficient, scenario coefficient, and threat coefficient. The encryption parameters are determined based on the encryption strength coefficient and the sensitivity coefficient. The key is determined based on the encryption parameters, the smart lock data is encrypted using the encryption algorithm, and then stored in the blockchain to obtain the smart lock on-chain data. When a participant needs to access the encrypted smart lock chain data, the participant's permission level is verified. If the verification is successful, the participant uses the private key and the key to decrypt the encrypted smart lock chain data and access it. Construct a scoring function for data privacy protection on the smart door lock chain, and dynamically adjust the encryption strength coefficient, encryption parameters, and access permissions based on the scoring function.

[0006] Furthermore, the process for setting the sensitivity coefficient is as follows:

[0007] in, Represents the sensitivity coefficient. This indicates the number of data types associated with the smart lock. express index, Indicates the first Weights of data for each type of smart door lock Indicates the first Sensitivity scores for each type of smart lock data.

[0008] Furthermore, the process for setting the threat coefficient is as follows:

[0009] in, Indicates the threat level. This represents the ratio of abnormal access frequency to normal access frequency. express The weight, Indicates the success rate of novel computational attack attempts. express The weight, .

[0010] Furthermore, the process for determining the encryption strength coefficient is as follows:

[0011] in, Indicates the encryption strength coefficient. Represents the sensitivity coefficient. express The weight, Represents the scene coefficient. express The weight, Indicates the threat level. express The weight, .

[0012] Furthermore, the encryption parameters include: key length and encryption speed; The key length is calculated as follows: ,in, Indicates the key length. Indicates the base key length. Indicates the encryption strength coefficient; The calculation process for the encryption speed is as follows: ,in, Indicates the baseline encryption speed. Indicates the dynamic attenuation coefficient. This represents the sensitivity coefficient.

[0013] Furthermore, a symmetric key is determined based on the encryption parameters, the smart lock data is encrypted using a symmetric encryption algorithm, and then the symmetric key is encrypted using an asymmetric encryption algorithm to obtain an asymmetric key. The encrypted smart lock data and the asymmetric key are then stored on the blockchain.

[0014] Furthermore, the process of verifying the permission levels of the participating parties is as follows: based on the sensitivity coefficient... and scene coefficient Determine the minimum permission level When the permission level of the participating party If the permission verification passes, then the verification fails; otherwise, the verification fails. express The grade coefficient, express The grade coefficient.

[0015] Furthermore, it also includes: constructing a scoring function for data privacy protection on the smart lock chain. :

[0016] in, This indicates the security score of the data on the smart door lock chain. express The weight, This indicates the response speed score. express The weight, This indicates the effectiveness score of access control. express The weight.

[0017] Furthermore, the security score of the data on the smart lock chain is determined based on the frequency of attacks and leaks of the data on the smart lock chain; The response speed score is determined by the time it takes to encrypt and decrypt data on the smart lock chain; The access control effectiveness score is determined based on the number of times unauthorized access occurs.

[0018] Furthermore, when the scoring function for data privacy protection on the smart lock chain is lower than the set scoring threshold, if the security score of the data on the smart lock chain is the lowest, the weight of the threat coefficient in the encryption strength coefficient is increased, and the weight of the sensitivity coefficient and scenario coefficient in the encryption strength coefficient is decreased; if the response speed score is the lowest, the attenuation coefficient of encryption speed in the encryption parameters is decreased or the baseline encryption speed in the encryption parameters is increased; if the access control effectiveness score is the lowest, the coefficients of each level of the lowest access level in the access verification process are increased.

[0019] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention constructs a dynamic encryption strength coefficient adjustment mechanism for real-time response to new computational attacks based on the privacy protection method of data on the smart door lock chain. This avoids the disadvantage of traditional algorithms being unable to respond to new computational attacks in a timely manner due to fixed encryption strategies. It ensures that the privacy data of the smart door lock will not be subject to reverse engineering due to the lag in encryption strategies, and significantly improves the timeliness of privacy protection of data on the smart door lock chain. (2) The privacy protection method for smart lock chain data in this invention dynamically adjusts the encryption parameters according to the sensitivity coefficient and scenario coefficient of the smart lock data. In low-sensitivity smart lock data and low-risk scenarios, relatively simplified encryption parameters are used to avoid lock response delay caused by over-encryption; while in high-sensitivity smart lock data and high-risk scenarios, enhanced encryption parameters are used to ensure data encryption security. This method of flexibly adjusting encryption parameters according to actual conditions breaks the limitations of traditional fixed encryption modes, enabling the encryption strategy to simultaneously meet the needs of response speed and data security, and greatly enhancing the dynamic adaptability of the privacy protection method. (3) The present invention constructs a multi-party collaborative privacy protection mechanism based on the privacy protection method of smart lock chain data, realizes the deep binding of data permissions of different participants with smart lock data encryption, ensures that each participant can only operate on smart lock chain data within its own permission scope, and guarantees the security of smart lock chain data. Attached Figure Description

[0020] Figure 1 This is a flowchart of the privacy protection method for data on a smart door lock chain according to the present invention. Detailed Implementation

[0021] The technical solution of the present invention will be further explained and described below with reference to the accompanying drawings.

[0022] like Figure 1 This is a flowchart of the privacy protection method for data on a smart lock chain according to the present invention. This method centers on smart lock data, is guided by the usage scenarios of smart locks, and relies on multi-party collaboration for protection. It protects privacy throughout the entire lifecycle of data on the smart lock chain, incorporating the generation, encryption, storage, access, and decryption of data on the smart lock chain into a unified protection system. By sensing data characteristics, scenarios, and permission information, the method automatically adjusts its strategy to ensure that protective actions are coordinated and focused on protecting the privacy of data on the smart lock chain, avoiding vulnerabilities caused by fragmented functions.

[0023] The privacy protection method of the present invention includes the following process: Collect smart lock data and set sensitivity levels based on the data type, such as user biometrics, unlocking records, temporary visitor keys, and permanent authorization keys. , ,in, This indicates that smart lock data is the most sensitive. This indicates the lowest level of sensitivity for smart lock data. Quantifying the sensitivity of smart lock data facilitates subsequent decisions on encryption strength coefficients and parameters based on specific values. Only by converting the ambiguous sensitivity levels into concrete values ​​can accurate calculations and comparisons be performed, allowing for the development of targeted protection strategies for smart lock data with different sensitivity levels and addressing the issue of uneven protection for different types of sensitive data.

[0024] The process for setting the sensitivity coefficient in this invention is as follows:

[0025] in, This indicates the number of data types associated with the smart lock. express index, Indicates the first Weights of data for each type of smart door lock Indicates the first Sensitivity scores for each type of smart lock data.

[0026] Scenario coefficients are set based on the usage scenarios of the smart lock. Specifically, usage scenario information is collected through the smart lock's sensors, such as using a human body sensor to determine whether it is in home mode, or using user settings to determine if there are temporary visitors. These usage scenarios are then coded, and scenario coefficients are set. , Generally, in home mode Outing mode When there are temporary visitors The reason for this configuration is that the data protection requirements of smart locks vary in different usage scenarios. By converting usage scenarios into scenario coefficients, which can be combined with data sensitivity coefficients to jointly determine the encryption strategy, the problem of incompatible encryption strategies in different usage scenarios can be solved.

[0027] Threat levels are set based on emerging computational attack indicators in smart lock data; specifically, real-time monitoring of emerging computational attack indicators in smart lock data, such as abnormal access frequencies and encryption cracking attempts, is conducted, and the threat level is assessed and a threat level is set. , This transforms abstract attack threats into concrete numerical values, making it easier to dynamically adjust encryption strength based on the threat level, respond promptly to new computational attacks, and address the issue of insufficient timeliness in privacy protection methods.

[0028] The process for setting the threat level in this invention is as follows:

[0029] in, This represents the ratio of abnormal access frequency to normal access frequency. express The weight, Indicates the success rate of novel computational attack attempts. express The weight, .

[0030] Based on the participants in the smart lock data interaction, permission levels are assigned to each participant. Specifically, the identity information and preset permission scope of each party involved in the smart lock data interaction, such as users, manufacturers, and property management, are collected and organized. Permission levels are then assigned to each participant. , Generally, user permission levels Manufacturer's authority level Property management authority levels This setting clarifies the scope of permissions for different participants, providing a basis for subsequent permission verification and resolving the issue of ambiguous permissions in multi-party collaborative protection.

[0031] The encryption strength coefficient is determined based on sensitivity, scenario, and threat factors, ensuring that it reflects the required encryption strength. Because different factors have varying encryption requirements, comprehensive calculation allows the encryption strength coefficient to better align with actual needs, resolving encryption mismatch issues caused by insufficient consideration of a single factor, and providing a clear basis for subsequent encryption execution.

[0032] The calculation process of the encryption strength coefficient in this invention is as follows:

[0033] in, Indicates the encryption strength coefficient. Represents the sensitivity coefficient. express The weight, Represents the scene coefficient. express The weight, Indicates the threat level. express The weight, .

[0034] The encryption parameters are determined based on the encryption strength coefficient and the sensitivity coefficient; specifically, the encryption parameters include: key length and encryption speed.

[0035] The key length is calculated as follows: ,in, Indicates the key length. Indicates the encryption strength coefficient. The base key length (B) may be dynamically adjusted based on several factors, such as the device's hardware capabilities (older locks with lower computing power have a smaller B, while newer devices with quantum chips have a larger B); updates to security standards; and changes in threats. The key length increases with the encryption strength coefficient because longer keys are more difficult to crack when higher encryption strength is required, thus improving the data security of smart locks.

[0036] The encryption speed is calculated as follows: ,in, Indicates the baseline encryption speed. Indicates the dynamic attenuation coefficient. This represents the sensitivity coefficient. When the sensitivity coefficient... and encryption strength coefficient When the sensitivity coefficient is small, the encryption speed is fast; when the sensitivity coefficient is small, the encryption speed is fast. and encryption strength coefficient When the data volume is large, the encryption speed is slower. This is because low-sensitivity data, with low encryption strength requirements, does not require overly complex encryption processes; fast encryption improves response speed. However, high-sensitivity data requires more sophisticated encryption, necessitating a reduction in speed to ensure security and address the issue of poor dynamic adaptability. The stronger the device's computing power, the faster the baseline encryption speed. The larger the value, the higher the scenario risk, and the greater the dynamic attenuation coefficient. The larger.

[0037] The key is determined based on the encryption parameters, and the smart lock data is encrypted using an encryption algorithm and stored on the blockchain to obtain the smart lock on-chain data; specifically, the symmetric key is determined based on the key length in the encryption parameters. The data of the smart lock is encrypted using a symmetric encryption algorithm, and the encrypted data is of length _____. ,but ,in, Indicates the use of a symmetric key Encryption is then performed. Symmetric encryption algorithms are fast and suitable for encrypting large amounts of data, meeting the high-frequency data update requirements of smart locks. Then, an asymmetric encryption algorithm is used to encrypt the symmetric key. Encryption is performed, and the public key for asymmetric encryption is denoted as . The private key is For symmetric keys The asymmetric key is obtained after encryption. ,but ,in, Indicates the use of a public key Encryption is performed. Asymmetric encryption algorithms offer high security by using a public key to encrypt the symmetric key. Only the party possessing the private key can decrypt the symmetric key, ensuring secure key transmission and management. Encryption strength determines the security level; the stronger the encryption, the better it resists attacks. Encryption speed ensures efficiency and meets the high-frequency data updates required by smart locks. The aforementioned hybrid encryption algorithm leverages the advantages of symmetric encryption's speed and asymmetric encryption's high security. This allows for the encryption of smart lock data. and asymmetric keys Store it on the blockchain and record relevant index information for subsequent access and verification.

[0038] When a participant needs to access data on the encrypted smart lock chain, their access level is verified. Once verified, the participant uses their private key and key to decrypt the data and gain access. Specifically, the participant sends an access request along with their identity identifier. and permission levels According to the sensitivity coefficient and scene coefficient Determine the minimum permission level When the participants' permission levels If the permission verification passes, then the verification fails; otherwise, the verification fails. express The grade coefficient, express The grade coefficient. Based on the data sensitivity coefficient. and scene coefficient Determine the minimum required permission level to match permission requirements with data characteristics and scenarios, ensuring that only participants with appropriate permissions can access the data, thus addressing the issue of weak collaborative protection capabilities. After successful permission verification, participants use their own private keys. symmetric key for encryption Decrypt to obtain ,in, Indicates the use of private key Perform the decryption operation. Then use... Encrypted data Decrypt to obtain the original data. Complete data access.

[0039] To ensure the long-term effectiveness of data privacy protection on the smart lock chain, a scoring function for data privacy protection on the smart lock chain is constructed, and the encryption strength coefficient, encryption parameters, and access permissions are dynamically adjusted according to the scoring function.

[0040] The scoring function for data privacy protection on the smart door lock chain in this invention :

[0041] in, This indicates the security score of the data on the smart door lock chain. express The weight, This indicates the response speed score. express The weight, This indicates the effectiveness score of access control. express The weight.

[0042] In one technical solution of the present invention, the security score of the data on the smart lock chain is determined based on the frequency of attacks and leaks of the data on the smart lock chain. Specifically, the total score of 100 is deducted by "attack count × 5 + leak count × 10". The response speed score is determined by the encryption and decryption time of the data on the smart lock chain. Specifically, the total score of 100 is deducted by "the ratio of the average encryption and decryption time to a preset threshold". The access control effectiveness score is determined based on the number of unauthorized accesses. Specifically, the total score of 100 is deducted by "unauthorized access count × 10".

[0043] In one technical solution of the present invention, when the scoring function for data privacy protection on the smart lock chain is lower than a set scoring threshold, if the security score of the data on the smart lock chain is the lowest, the weight of the threat coefficient in the encryption strength coefficient is increased, and the weights of the sensitivity coefficient and scenario coefficient in the encryption strength coefficient are decreased, thereby improving the anti-attack redundancy of the encrypted data and forming a security closed loop with the behavior calculation of blockchain verification; if the response speed score is the lowest, the attenuation coefficient of encryption speed in the encryption parameters is reduced or the baseline encryption speed in the encryption parameters is increased, thereby reducing the generation time of encryption and decryption while maintaining encryption strength, and adapting to the high-frequency interaction needs of smart locks; if the access control effectiveness score is the lowest, the coefficients of each level of the lowest access level in the access verification process are increased, thereby increasing the strictness of judging unauthorized behavior.

[0044] The scoring function for data privacy protection on the smart lock chain is recalculated based on the updated encryption strength coefficient, encryption parameters, and minimum permission level until the recalculated scoring function exceeds the set scoring threshold.

[0045] This invention constructs a dynamic encryption strength coefficient adjustment mechanism based on a privacy protection method for data on a smart lock chain, responding in real time to novel computational attacks. This mechanism can quickly analyze the threat level of attacks on the current encryption strategy and generate encryption strength coefficient adjustment instructions. Because the data on the smart lock chain is frequently updated, it can iterate in real time according to the dynamic encryption strength coefficient adjustment mechanism. This avoids the drawback of traditional algorithms that cannot respond to new attacks in a timely manner due to fixed encryption strategies. It ensures that long-term stored data on the smart lock chain is not vulnerable to reverse engineering due to outdated encryption strategies, significantly improving the timeliness of privacy protection. This invention presents a privacy protection method for data on a smart lock chain. The method dynamically adjusts encryption parameters based on the sensitivity and scenario levels of the smart lock data. This allows for accurate identification of the sensitivity level of data on the smart lock chain, such as distinguishing between the different sensitivity levels of temporary visitor keys and permanent authorization keys. It also accurately determines the lock's usage scenario, such as home mode or away mode. Encryption operations are performed using these parameters. In low-sensitivity data and low-risk scenarios, relatively simplified encryption parameters are used to avoid over-encryption leading to smart lock response delays. In high-sensitivity data and high-risk scenarios, enhanced encryption parameters are used to ensure the security of smart lock data encryption. This flexible adjustment approach breaks the limitations of traditional algorithms with fixed encryption modes, enabling encryption strategies to simultaneously meet the needs of system response speed and data security, greatly enhancing the dynamic adaptability of data privacy protection on the smart lock chain.

[0046] This invention constructs a multi-party collaborative privacy protection mechanism based on a privacy protection method for data on a smart lock chain, and formulates corresponding encryption and decryption rules to ensure that each participant can only operate on the data within its authorized scope. During the data encryption process, the participant's permission information is embedded, generating encrypted data associated with those permissions. When a participant attempts to access or decrypt data, the operation can only be successfully completed if its permissions match the permission information embedded in the encrypted data. This mechanism blocks the possibility of permission abuse at the encryption level. For example, when an administrator attempts to access user data without authorization, the decryption operation cannot be completed because its permissions do not match the permissions required by the encrypted data. Compared to traditional algorithms that lack a multi-party collaborative privacy protection mechanism and where permissions are disconnected from the encryption process, this invention effectively strengthens the collaborative protection capability in multi-subject data interaction through deep binding of permissions and encryption, ensuring the security of data privacy protection on the smart lock chain.

[0047] In summary, the privacy protection method for data on the smart lock chain of this invention significantly improves the privacy protection level of data on the smart lock chain and enhances the security and confidentiality of data on the smart lock chain.

[0048] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A privacy protection method based on data on a smart door lock chain, characterized in that, The specific process is as follows: Collect smart lock data and set sensitivity coefficients based on the type of smart lock data; Set scenario coefficients based on the usage scenarios of smart door locks; Threat levels are set based on new computational attack patterns in smart lock data; Assign permission levels to each participant in the smart lock data interaction process. The encryption strength coefficient is determined based on the sensitivity coefficient, scenario coefficient, and threat coefficient. The encryption parameters are determined based on the encryption strength coefficient and the sensitivity coefficient. The key is determined based on the encryption parameters, the smart lock data is encrypted using the encryption algorithm, and then stored in the blockchain to obtain the smart lock on-chain data. When a participant needs to access the encrypted smart lock chain data, the participant's permission level is verified. If the verification is successful, the participant uses the private key and the key to decrypt the encrypted smart lock chain data and access it. Construct a scoring function for data privacy protection on the smart door lock chain, and dynamically adjust the encryption strength coefficient, encryption parameters, and access permissions based on the scoring function.

2. The privacy protection method based on data on a smart door lock chain according to claim 1, characterized in that, The process for setting the sensitivity coefficient is as follows: in, Represents the sensitivity coefficient. This indicates the number of data types associated with the smart lock. express index, Indicates the first Weights of data for each type of smart door lock Indicates the first Sensitivity scores for each type of smart lock data.

3. The privacy protection method based on data on a smart door lock chain according to claim 1, characterized in that, The process for setting the threat level is as follows: in, Indicates the threat level. This represents the ratio of abnormal access frequency to normal access frequency. express The weight, Indicates the success rate of novel computational attack attempts. express The weight, .

4. The privacy protection method based on data on a smart door lock chain according to claim 1, characterized in that, The process for determining the encryption strength coefficient is as follows: in, Indicates the encryption strength coefficient. Represents the sensitivity coefficient. express The weight, Represents the scene coefficient. express The weight, Indicates the threat level. express The weight, .

5. A privacy protection method based on data on a smart door lock chain according to claim 1, characterized in that, The encryption parameters include: key length and encryption speed; The key length is calculated as follows: ,in, Indicates the key length. Indicates the base key length. Indicates the encryption strength coefficient; The calculation process for the encryption speed is as follows: ,in, Indicates the baseline encryption speed. Indicates the dynamic attenuation coefficient. This represents the sensitivity coefficient.

6. A privacy protection method based on data on a smart door lock chain according to claim 1, characterized in that, The symmetric key is determined based on the encryption parameters. The smart lock data is then encrypted using a symmetric encryption algorithm. The symmetric key is then encrypted using an asymmetric encryption algorithm to obtain the asymmetric key. Finally, the encrypted smart lock data and the asymmetric key are stored on the blockchain.

7. A privacy protection method based on data on a smart door lock chain according to claim 1, characterized in that, The process of verifying the permission levels of the participants is as follows: based on the sensitivity coefficient... and scene coefficient Determine the minimum privilege level When the permission level of the participating party If the permission verification passes, then the verification fails; otherwise, the verification fails. express The grade coefficient, express The grade coefficient.

8. A privacy protection method based on data on a smart door lock chain according to claim 1, characterized in that, Also includes: Constructing a scoring function for data privacy protection on a smart door lock chain : in, This indicates the security score of the data on the smart door lock chain. express The weight, This indicates the response speed score. express The weight, This indicates the effectiveness score of access control. express The weight.

9. A privacy protection method based on data on a smart door lock chain according to claim 8, characterized in that: The security score of the data on the smart lock chain is determined based on the frequency of attacks and leaks to the data on the smart lock chain. The response speed score is determined by the time it takes to encrypt and decrypt data on the smart lock chain; The access control effectiveness score is determined based on the number of times unauthorized access occurs.

10. A privacy protection method based on data on a smart door lock chain according to claim 8, characterized in that, When the scoring function for data privacy protection on the smart lock chain is lower than the set scoring threshold, if the security score of the data on the smart lock chain is the lowest, the weight of the threat coefficient in the encryption strength coefficient will be increased, and the weight of the sensitivity coefficient and the scenario coefficient in the encryption strength coefficient will be decreased. If the response speed score is the lowest, reduce the attenuation coefficient of encryption speed in the encryption parameters or increase the base encryption speed in the encryption parameters; if the access control effectiveness score is the lowest, increase the coefficients of each level of the lowest access level in the access verification process.

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