Encryption method, system and device based on RSA artificial intelligence and storage medium

Abstract

The invention discloses an encryption method, system and device based on RSA artificial intelligence and a storage medium, belongs to the technical field of encryption, and solves the technical problems that a traditional encryption method is low in efficiency when processing a large amount of industrial internet data and is difficult to deal with complex and variable security threats. The method comprises the steps of performing feature extraction on to-be-encrypted data by using a machine learning algorithm; a machine learning algorithm and an RSA encryption algorithm are combined to generate a self-adaptive encryption strategy; performing intelligent generation and management on the RSA key by using an artificial intelligence technology; performing encryption processing on the to-be-encrypted data by using the self-adaptive encryption strategy to obtain encrypted data; a secure transmission protocol is used to ensure that the encrypted data is not leaked or tampered in the transmission process, and a secure communication protocol and technology are adopted to ensure the security of the encrypted data in network transmission; before storage, RSA encryption processing is carried out, and proper access control and encryption measures are taken; and the access of the stored encrypted data is subjected to refined management in combination with an artificial intelligence technology.

Description

Technical Field

[0001] The present invention relates to the field of encryption technology, and more specifically, to an encryption method, system, device and storage medium based on RSA artificial intelligence. Background Art

[0002] With the rapid development of industrial Internet, information exchange between enterprises has become increasingly frequent. However, this is accompanied by information leakage and data security issues, which pose potential risks to the business secrets of enterprises and user privacy. Traditional encryption methods are inefficient when processing large amounts of industrial Internet data and are difficult to cope with complex and changing security threats. Therefore, a more efficient and intelligent industrial Internet security encryption method is needed. Summary of the invention

[0003] The technical problem to be solved by the present invention is to address the above-mentioned deficiencies in the prior art. One purpose of the present invention is to provide an encryption method based on RSA artificial intelligence.

[0004] The second purpose of the present invention is to provide an encryption system based on RSA artificial intelligence.

[0005] A third object of the present invention is to provide a computer device.

[0006] A fourth objective of the present invention is to provide a computer storage medium.

[0007] In order to achieve the above-mentioned purpose one, the present invention provides an encryption method based on RSA artificial intelligence, comprising the following steps:

[0008] Step 1. Use machine learning algorithms to extract features from encrypted data to obtain data features;

[0009] Step 2. Combine machine learning algorithms and RSA encryption algorithms to dynamically generate adaptive encryption strategies based on data characteristics;

[0010] Step 3. Use artificial intelligence technology to intelligently generate and manage RSA keys to ensure the security and difficulty of key cracking;

[0011] Step 4. Using the generated adaptive encryption strategy, the RSA algorithm is used to encrypt the data to be encrypted to obtain encrypted data;

[0012] Step 5. Combine encrypted data with secure transmission protocols to ensure that the encrypted data will not be leaked or tampered with during transmission, and use secure communication protocols and technologies to ensure the security of encrypted data during network transmission;

[0013] Step 6. Before storage, perform RSA encryption on the encrypted data and take appropriate access control and encryption measures on the storage medium;

[0014] Step 7. Combine artificial intelligence technology to establish a role-based access control model to perform refined management of access to stored encrypted data.

[0015] As a further improvement, in step 1, it also includes:

[0016] Analyze data attributes and identify key features in the data;

[0017] Data preprocessing technology is used to convert the data to be encrypted into a form suitable for processing by machine learning algorithms to ensure the accuracy of feature extraction.

[0018] Furthermore, in step 2, it also includes:

[0019] According to the changes in data characteristics, adjust encryption parameters to match different types of data to ensure the best encryption effect;

[0020] Integrate historical encryption experience and establish encryption models targeting specific data features to improve encryption efficiency and accuracy.

[0021] Furthermore, in step 3, it also includes:

[0022] Machine learning-based model optimization continuously updates and adjusts RSA keys to adapt to changing security needs and threats;

[0023] Automatically rotate or update RSA keys to reduce the risk of RSA keys being cracked.

[0024] Furthermore, in step 4, it also includes:

[0025] Ensure that the encryption process complies with relevant security standards and protocols and avoid common encryption attack methods;

[0026] Verify the encrypted data to ensure data integrity and encryption correctness.

[0027] Furthermore, in step 5, it also includes: monitoring the security status of the data transmission process in real time, and promptly discovering and handling potential security threats.

[0028] Furthermore, in step 6, it also includes:

[0029] Combine artificial intelligence technology to intelligently manage stored encrypted data, identify abnormal access behaviors and respond accordingly;

[0030] Use secure storage technology to encrypt databases or secure storage devices to ensure that data is effectively protected even in a static state;

[0031] In step 7, it also includes:

[0032] Implement multi-factor authentication mechanisms to improve the security of data access and reduce the risk of unauthorized data access;

[0033] Dynamically adjust access permissions based on real-time data usage and access history to adapt to the timely changing needs of different users.

[0034] In order to achieve the above-mentioned second objective, the present invention provides an encryption system based on RSA artificial intelligence, comprising:

[0035] A feature extraction module, used to extract features from encrypted data using a machine learning algorithm to obtain data features;

[0036] The encryption strategy module is used to combine the machine learning algorithm and the RSA encryption algorithm to dynamically generate an adaptive encryption strategy based on data characteristics;

[0037] RSA key module, which uses artificial intelligence technology to intelligently generate and manage RSA keys to ensure the security and hardness of the keys;

[0038] An encryption module is used to utilize the generated adaptive encryption strategy and adopt the RSA algorithm to encrypt the data to be encrypted to obtain encrypted data;

[0039] The transmission module is used to combine encrypted data with secure transmission protocols to ensure that the encrypted data will not be leaked or tampered with during transmission, and to use secure communication protocols and technologies to ensure the security of encrypted data during network transmission;

[0040] The storage module is used to perform RSA encryption on the encrypted data before storage, and to take appropriate access control and encryption measures on the storage medium;

[0041] The permission module is used to combine artificial intelligence technology to establish a role-based access control model and perform refined management of access to stored encrypted data.

[0042] In order to achieve the third objective above, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned RSA artificial intelligence-based encryption method when executing the computer program.

[0043] In order to achieve the above-mentioned fourth objective, the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the above-mentioned RSA artificial intelligence-based encryption method is implemented.

[0044] Beneficial Effects

[0045] Compared with the prior art, the present invention has the following advantages:

[0046] The method of the present invention combines the RSA encryption algorithm and artificial intelligence technology to realize data characterization encryption, adaptive encryption and other functions, improve encryption efficiency and security, and is suitable for the secure transmission and storage of large-scale industrial Internet data. At the same time, through intelligent key management and access control, the security level of data is further improved, which helps to prevent various security threats and attacks. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0048] The present invention will be further described below with reference to the specific embodiments in the accompanying drawings.

[0049] See also Figure 1 , an encryption method based on RSA artificial intelligence, comprising the following steps:

[0050] Step 1. Use machine learning algorithms to extract features from encrypted data to obtain data features;

[0051] Step 2. Combine machine learning algorithms and RSA encryption algorithms to dynamically generate adaptive encryption strategies based on data characteristics;

[0052] Step 3. Use artificial intelligence technology to intelligently generate and manage RSA keys to ensure the security and difficulty of key cracking;

[0053] Step 4. Using the generated adaptive encryption strategy, the RSA algorithm is used to encrypt the data to be encrypted to obtain encrypted data;

[0054] Step 5. Combine encrypted data with secure transmission protocols to ensure that the encrypted data will not be leaked or tampered with during transmission, and use secure communication protocols and technologies to ensure the security of encrypted data during network transmission;

[0055] Step 6. Before storage, perform RSA encryption on the encrypted data and take appropriate access control and encryption measures on the storage medium;

[0056] Step 7. Combine artificial intelligence technology to establish a role-based access control model to perform refined management of access to stored encrypted data.

[0057] In step 1, data features include data distribution, frequency distribution, and correlation. To implement data feature extraction in Java, various machine learning libraries and tools can be used.

[0058] Also included in step 1:

[0059] Analyze data attributes and identify key features in the data, such as sensitive information and important indicators. Analyzing data attributes usually needs to be done based on specific data types and requirements, such as identifying the maximum, minimum, and average values ​​in the data.

[0060] Using data preprocessing techniques, including common data preprocessing steps such as data loading, processing missing values, and normalization, the encrypted data is converted into a form suitable for machine learning algorithm processing to ensure the accuracy of feature extraction. In Java, various libraries and techniques can be used for data preprocessing to ensure that the data is suitable for processing by machine learning algorithms.

[0061] In step 2, it also includes:

[0062] According to the changes in data characteristics, the encryption parameters are adjusted to match different types of data, that is, the corresponding encryption strength is set according to different data characteristics. If the data has multiple characteristics at the same time, the encryption strength corresponding to the data feature with the strongest encryption strength will be selected to ensure the best encryption effect.

[0063] It is also possible to integrate historical encryption experience and establish encryption models for specific data features to improve encryption efficiency and accuracy. Specifically, a historical encryption experience dataset is constructed, and specific data features and corresponding encryption strengths are added as training data. The dataset is used to train the encryption model, and finally the encryption strength of the data to be encrypted is predicted based on the model.

[0064] In step 3, you can use the linear regression model from the Weka library and Java’s built-in cryptographic library to generate and manage RSA key pairs.

[0065] Furthermore, step 3 also includes:

[0066] Based on machine learning model optimization, RSA keys are continuously updated and adjusted to adapt to changing security needs and threats. Specifically, a manager class can be created to handle the generation, update, and dynamic adjustment of the security level of RSA keys. The manager class includes the function of predicting the key security level using encryption model training.

[0067] RSA keys can also be automatically rotated or updated. Specifically, the key security level can be dynamically generated, and new key pairs can be dynamically generated for use. When security threats are discovered, key rotation, periodic key updates, and retraining of encryption models are triggered to reduce the risk of RSA keys being cracked.

[0068] In step 4, you can create an IntelligentRSAKeyManager class, which contains methods for establishing a security model, determining the security level of dynamic keys, generating and using RSA key pairs, and encrypting and decrypting data.

[0069] In step 4, also include:

[0070] Ensure that the encryption process complies with relevant security standards and protocols to avoid common encryption attack methods.

[0071] Verify the encrypted data to ensure data integrity and encryption correctness. You can verify the encrypted data to ensure data integrity and encryption correctness by adding the verifyEncryptedData method. This process includes decrypting the data using the private key, calculating the digest of the original data and the decrypted data, and finally comparing the two to confirm encryption correctness and data integrity.

[0072] In step 5, it also includes: real-time monitoring of the security status of the data transmission process, and timely detection and handling of potential security threats.

[0073] In step 6, it also includes:

[0074] Combine artificial intelligence technology to intelligently manage stored encrypted data, identify abnormal access behaviors and respond accordingly;

[0075] Use secure storage technology to encrypt databases or secure storage devices to ensure that data is effectively protected even in a static state.

[0076] In step 7, it also includes:

[0077] Implement multi-factor authentication mechanisms, such as using at least two combinations of the user's username and password, mobile phone number, fingerprint data, and SMS verification code for authentication, to improve the security of data access and reduce the risk of unauthorized data access.

[0078] Furthermore, the access rights are dynamically adjusted based on the real-time data usage and access history to meet the changing needs of different users. Specifically, it is possible to dynamically determine whether a user has access rights based on the real-time data usage and access history. If the number of accesses is less than 200, the user has access rights; if the number of accesses in a short period of time is greater than the limit, the user has access rights; if the user's access history cannot be found, the user does not have access rights by default.

[0079] In the transmission and storage of device data in the industrial Internet, the encryption method of the present invention can dynamically adjust the encryption strategy according to data characteristics, and combine secure transmission and storage technologies to ensure the security of data transmission and the integrity and confidentiality of data during the storage process.

[0080] An encryption system based on RSA artificial intelligence, comprising:

[0081] A feature extraction module, used to extract features from encrypted data using a machine learning algorithm to obtain data features;

[0082] The encryption strategy module is used to combine the machine learning algorithm and the RSA encryption algorithm to dynamically generate an adaptive encryption strategy based on data characteristics;

[0083] RSA key module, which uses artificial intelligence technology to intelligently generate and manage RSA keys to ensure the security and hardness of the keys;

[0084] An encryption module is used to utilize the generated adaptive encryption strategy and adopt the RSA algorithm to encrypt the data to be encrypted to obtain encrypted data;

[0085] The transmission module is used to combine encrypted data with secure transmission protocols to ensure that the encrypted data will not be leaked or tampered with during transmission, and to use secure communication protocols and technologies to ensure the security of encrypted data during network transmission;

[0086] The storage module is used to perform RSA encryption on the encrypted data before storage, and to take appropriate access control and encryption measures on the storage medium;

[0087] The permission module is used to combine artificial intelligence technology to establish a role-based access control model and perform refined management of access to stored encrypted data.

[0088] A computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the above-mentioned encryption method based on RSA artificial intelligence is implemented.

[0089] A computer-readable storage medium stores a computer program, which implements the above-mentioned RSA artificial intelligence-based encryption method when executed by a processor.

[0090] The above are only preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the structure of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. An encryption method based on RSA artificial intelligence, characterized in that: The following steps are involved: Step 1. Use machine learning algorithms to extract features from encrypted data to obtain data features; Step 2. Combine machine learning algorithms and RSA encryption algorithms to dynamically generate adaptive encryption strategies based on data characteristics; Step 3. Use artificial intelligence technology to intelligently generate and manage RSA keys to ensure the security and difficulty of key cracking; Step 4. Using the generated adaptive encryption strategy, the RSA algorithm is used to encrypt the data to be encrypted to obtain encrypted data; Step 5. Combine encrypted data with secure transmission protocols to ensure that the encrypted data will not be leaked or tampered with during transmission, and use secure communication protocols and technologies to ensure the security of encrypted data during network transmission; Step 6. Before storage, perform RSA encryption on the encrypted data and take appropriate access control and encryption measures on the storage medium; Step 7. Combine artificial intelligence technology to establish a role-based access control model to perform refined management of access to stored encrypted data.

2. The encryption method based on RSA artificial intelligence according to claim 1, characterized in that: In step 1, it also includes: Analyze data attributes and identify key features in the data; Data preprocessing technology is used to convert the data to be encrypted into a form suitable for processing by machine learning algorithms to ensure the accuracy of feature extraction.

3. The encryption method based on RSA artificial intelligence according to claim 1, characterized in that: In step 2, it also includes: According to the changes in data characteristics, adjust encryption parameters to match different types of data to ensure the best encryption effect; Integrate historical encryption experience and establish encryption models targeting specific data features to improve encryption efficiency and accuracy.

4. The encryption method based on RSA artificial intelligence according to claim 1, characterized in that: In step 3, it also includes: Machine learning-based model optimization continuously updates and adjusts RSA keys to adapt to changing security needs and threats; Automatically rotate or update RSA keys to reduce the risk of RSA keys being cracked.

5. The encryption method based on RSA artificial intelligence according to claim 1, characterized in that: In step 4, it also includes: Ensure that the encryption process complies with relevant security standards and protocols and avoid common encryption attack methods; Verify the encrypted data to ensure data integrity and encryption correctness.

6. The encryption method based on RSA artificial intelligence according to claim 1, characterized in that: In step 5, it also includes: real-time monitoring of the security status of the data transmission process, and timely detection and handling of potential security threats.

7. The encryption method based on RSA artificial intelligence according to claim 1, characterized in that: In step 6, it also includes: Combine artificial intelligence technology to intelligently manage stored encrypted data, identify abnormal access behaviors and respond accordingly; Use secure storage technology to encrypt databases or secure storage devices to ensure that data is effectively protected even in a static state; In step 7, it also includes: Implement multi-factor authentication mechanisms to improve the security of data access and reduce the risk of unauthorized data access; Dynamically adjust access permissions based on real-time data usage and access history to adapt to the timely changing needs of different users.

8. An encryption system based on RSA artificial intelligence, characterized in that: include: A feature extraction module, used to extract features from encrypted data using a machine learning algorithm to obtain data features; The encryption strategy module is used to combine the machine learning algorithm and the RSA encryption algorithm to dynamically generate an adaptive encryption strategy based on data characteristics; RSA key module, which uses artificial intelligence technology to intelligently generate and manage RSA keys to ensure the security and hardness of the keys; An encryption module is used to utilize the generated adaptive encryption strategy and adopt the RSA algorithm to encrypt the data to be encrypted to obtain encrypted data; The transmission module is used to combine encrypted data with secure transmission protocols to ensure that the encrypted data will not be leaked or tampered with during transmission, and to use secure communication protocols and technologies to ensure the security of encrypted data during network transmission; The storage module is used to perform RSA encryption on the encrypted data before storage, and to take appropriate access control and encryption measures on the storage medium; The permission module is used to combine artificial intelligence technology to establish a role-based access control model and perform refined management of access to stored encrypted data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, an RSA artificial intelligence-based encryption method as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, an RSA artificial intelligence-based encryption method as described in any one of claims 1 to 7 is implemented.

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