Network information protection method based on big data analysis

Abstract

The invention relates to the technical field of network information protection based on big data analysis, and discloses a network information protection method based on big data analysis. By establishing a transmission channel identification system, the uniqueness identification problem of data such as transmission content types, source addresses, target addresses, timestamps and the like in the transmission process is solved, so that more accurate encryption protection is provided. And a user-defined generation function is combined with the multi-dimensional information to generate a unique transmission channel identifier, so that the uniqueness of each transmission process in a big data environment is ensured. The character string characters are subjected to weighted mapping through the hash function, so that hash collision is avoided, and the uniqueness of the identifier is ensured. The unpredictability of an output value is further increased by using a high-dimensional mapping function and a large prime number, the encryption security is improved, and man-in-the-middle attack and replay attack are effectively prevented. According to the scheme, accurate encryption control is ensured, and the security in a big data environment is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of network information protection based on big data analysis, and specifically provides a network information protection method based on big data analysis. Background Art

[0002] With the rapid development of network technology, the Internet has become an essential part of modern society. Against this backdrop, network security has become a crucial issue in the daily work of various organizations and individuals. In particular, in the face of a big data environment, the protection of network information and privacy security have become urgent problems to be solved. Various threats that may occur during data transmission, such as data theft, tampering, hijacking, etc., all need to be protected through technical means. Currently, most existing technologies face multiple challenges, such as insufficient encryption protection, unstable data transmission, vulnerabilities in encryption algorithms, unreasonable path selection, etc.

[0003] The network information protection methods in the prior art mainly focus on traditional encryption and identity authentication mechanisms. Many methods use static encryption algorithms, such as AES, to protect data transmission. Although these methods can provide basic protection, they often prove insufficient when faced with a dynamically changing network environment and increasingly sophisticated attack methods. Traditional encryption methods lack flexibility and adaptability in the encryption intensity of data and cannot adjust the encryption intensity according to the real-time state of the transmission network and the sensitivity of the data. In addition, static encryption algorithms will encounter efficiency problems in encryption and decryption when dealing with large-scale data streams, thus affecting network performance.

[0004] Although the existing technologies have improved the ability to protect network information to a certain extent, they still prove insufficient when dealing with a dynamic network environment and complex attack methods. Traditional methods such as static encryption, path selection, and encryption intensity adjustment have problems such as poor flexibility and insufficient real-time performance when faced with the variability of the modern network environment. Therefore, this case aims to propose a network information protection method based on big data analysis, which includes dynamic encryption, path selection, encryption intensity adjustment, etc. based on big data analysis. Summary of the Invention

[0005] The present invention provides a network information protection method based on big data analysis, which helps to solve the problems mentioned in the above background art.

[0006] The present invention provides the following technical solution: A network information protection method based on big data analysis, including:

[0007] S1. Encryption of the dynamic transmission channel:

[0008] S11. Establish a transmission channel identification system:

[0009] Obtain the type of the transmitted content, denoted as ContentType;

[0010] The types of the transmitted content include sensitive content Sensitive, public content Public, and general content General;

[0011] Obtain the source address of the transmission, denoted as Source;

[0012] Obtain the destination address of the transmission, denoted as Destination;

[0013] Obtain the timestamp during the transmission, denoted as Timestamp;

[0014] Set a custom generation function, denoted as g, where g is a multi-dimensional mapping function based on ContentType, Source, Destination, and Timestamp, specifically:

[0015]

[0016] Among them, is the mapping function, specifically:

[0017]

[0018] Among them, Hash(·) is a custom hash function that converts the input string into a fixed-length numerical value, specifically:

[0019] Set a large prime number, denoted as P1;

[0020]

[0021] Among them, X i is the ASCII value of the i-th character of the string X; α i is the weight coefficient of the i-th character of the string X; n is the total number of characters of the string X; mod is the modulo operation;

[0022] Record the calculation result of the mapping function as the intermediate value V;

[0023] Set the high-dimensional mapping function, specifically:

[0024] Set a large prime number, denoted as P2, and P2 ≠ P1;

[0025]

[0026] Among them, sin(V), cos(V), and log(V + 1) are three mathematical transformations of the intermediate value V, generating non-linear changes;

[0027] Take the calculation result of the high - level mapping function as the unique identifier, denoted as UID;

[0028] S12. Analyze the type of transmission content in real - time;

[0029] S13. Adjust the encryption strength adaptively;

[0030] S2. Secure transmission based on blockchain;

[0031] S3. Intelligent management of end - to - end encryption.

[0032] Optionally, the real - time analysis of the type of transmission content specifically includes:

[0033] Set an encryption requirement function f(ContentType) based on the type of transmission content. This function uses the linear weighting method, specifically:

[0034]

[0035] Among them, β1, β2, and β3 are the weight coefficients of various types of content; is an indicator function. If the input condition is true, the value is 1; if the input condition is false, the value is 0.

[0036] Optionally, the adaptive adjustment of the encryption strength specifically includes:

[0037] Obtain the transmission network latency, denoted as NetworkLatency;

[0038] Obtain the transmission packet loss rate, denoted as PacketLoss;

[0039] Obtain the transmission network bandwidth, denoted as Bandwidth;

[0040] Obtain the reliability of the transmission network path, denoted as Reliability;

[0041] Set a network status risk assessment function to calculate the network status risk level and adjust the encryption strength, specifically:

[0042] The network status risk assessment function is:

[0043]

[0044] Among them, γ1, γ2, γ3, and γ4 are network status factors for adjusting the risk assessment;

[0045] Set three levels of encryption, namely:

[0046] ψ: High - strength encryption;

[0047] φ: Medium - strength encryption;

[0048] Low - intensity encryption;

[0049] Adjust the encryption strength according to the calculation result of the network status risk assessment function:

[0050] Record the calculation result of the network status risk assessment function as R;

[0051]

[0052] Among them, EncryptionStrength is the encryption strength.

[0053] Optionally, the three - intensity encryption specifically includes:

[0054] The high - intensity encryption ψ is specifically:

[0055] Set a large prime number, denoted as P3, and P3≠P2;

[0056] Obtain the total number of data blocks during transmission, denoted as ψ n ;

[0057]

[0058] Among them, DataBit i is the number of bits of the i - th data block; k i is the weight coefficient of the i - th data block; The medium - intensity encryption φ is specifically:

[0059] Set a large prime number, denoted as P4, and P4≠P3;

[0060] Set the number of data blocks required for medium encryption, denoted as φ n ;

[0061]

[0062] Low - intensity encryption Specifically:

[0063] Set a large prime number, denoted as P5, and P5≠P4;

[0064] Set the minimum number of data blocks required for low - intensity encryption, denoted as

[0065]

[0066] Optionally, the blockchain - based secure transmission specifically includes:

[0067] S21. Create a blockchain data transmission node:

[0068] Each time data is transmitted, a transmission block is generated, denoted as B, which contains the following content:

[0069] B = (UID, EncryptedData, Timestamp, Source, Destination, Nonce);

[0070] Among them, EncryptedData is the encrypted data; Nonce is a random value to ensure the non-repeatability of the data transmission process;

[0071] S22. The smart contract controls the data transmission permission:

[0072] Obtain the user credentials, denoted as UserCredentials;

[0073] Set a random verification algorithm and perform the transmission verification V(UID, UserCredentials), specifically:

[0074] Set a large prime number, denoted as P6, and P6 ≠ P5;

[0075] V(UID, UserCredentials) = (h(UID, UserCredentials, Timestamp)) mod P6;

[0076] Among them, h(·) is a hash function;

[0077] If the result of the random verification algorithm V(UID, UserCredentials) is zero, the transmission is allowed;

[0078] If the result of the random verification algorithm V(UID, UserCredentials) is not zero, the transmission is allowed;

[0079] S23. Verification and confirmation after transmission:

[0080] When verifying the integrity of the block transmission, perform the verification through the reverse hash function:

[0081]

[0082] Among them, h(B) and h(B') are the hash values of the transmission block respectively. If the two are equal, it is determined that the data has not been tampered with. If the two are not equal, it is determined that the data has been tampered with; B' is the block received by the target node.

[0083] Optionally, the intelligent management of end-to-end encryption specifically includes:

[0084] S31. Intelligent selection of the transmission path:

[0085] Set the set of transmission paths, denoted as Paths;

[0086] Obtain all transmission paths and add them to the set of transmission paths Paths;

[0087] Based on the path selection optimization function P(ContentType), calculate the optimal transmission path:

[0088]

[0089] where, is the basic cost function of the transmission path p; is the content sensitivity function of the transmission path p;

[0090] S32. Real-time encryption policy adjustment:

[0091] Based on the network transmission dynamic monitoring data, set the encryption level adjustment function, specifically:

[0092] A(NetworkStatus,ContentType) = R(NetworkStatus)1 + f(ContentType)·δ2;

[0093] where, δ1 and δ2 are the weight coefficients of the encryption strength; A(NetworkStatus,ContentType) is used to adjust the encryption strength;

[0094] S33. Key management and update mechanism:

[0095] Obtain the current timestamp, denoted as Timestamp current ;

[0096] Obtain the currently used encryption key, denoted as K old ;

[0097] Obtain the risk score of the transmission path, denoted as PathRisk;

[0098] Set a large prime number, denoted as P7, and P7 ≠ P6;

[0099] Generate a new key by combining the transmission path risk and the current timestamp, and the key update function is specifically:

[0100]

[0101] Optionally, the basic cost function specifically includes:

[0102] Obtain the latency of the transmission path p, denoted as Latency(p);

[0103] Obtain the packet loss rate of the transmission path p, denoted as PacketLoss(p);

[0104] Obtain the bandwidth of the transmission path p, denoted as Bandwidth(p);

[0105] The basic cost function is specifically as follows:

[0106]

[0107] Among them, λ1, λ2, and λ3 are the weighting coefficients of each factor.

[0108] Optionally, the content sensitivity function specifically includes:

[0109]

[0110] The present invention has the following beneficial effects:

[0111] 1. By establishing a transmission channel identification system, the problem of unique identification of data such as the type of transmission content, source address, destination address, and timestamp during the transmission process is solved, and more precise encryption protection is provided. Through a custom generation function, combined with the multi-dimensional mapping of the type of transmission content, source address, destination address, and timestamp, a unique transmission channel identifier is generated. This identifier ensures the uniqueness of each transmission channel in the big data environment, enabling each transmission process to obtain precise encryption control. Specifically, each character of the string is weighted and mapped through a hash function, avoiding the problem of hash collisions and ensuring the uniqueness of the identifier. Combining the use of a high-dimensional mapping function and large prime numbers further increases the unpredictability of the output value, enhances the security of encryption, and thus effectively prevents man-in-the-middle attacks and replay attacks.

[0112] 2. By analyzing the transmission content type in real time through steps, the problem that traditional encryption schemes cannot dynamically adjust the encryption intensity according to different content types is solved, thereby improving the encryption efficiency and the accuracy of data protection. In traditional network information protection, a fixed encryption method is usually used to encrypt all transmitted data. This static encryption method cannot adapt to the security requirements of different data. To address this issue, this solution designs an encryption requirement function based on the transmission content type. This function uses a linear weighting method, considering the encryption requirements and complexity of the content, and sets different encryption intensity requirements for different types of content. By setting the weight coefficients, the system can automatically adjust the encryption strategy according to the content type, such as sensitive data, public data, and general data, to ensure that highly sensitive data obtains sufficient encryption protection without over-encrypting public data, thus optimizing the use of encryption resources. During this process, the introduction of the indicator function further improves the flexibility of the encryption requirements, enabling the encryption requirement function to accurately judge the encryption intensity requirements of different transmitted content. For example, for sensitive content, the indicator function will be in the "true" state, triggering a higher encryption intensity; while for public content, the indicator function is in the "false" state, correspondingly reducing the encryption intensity to ensure that the transmission efficiency is not affected. Through the design of this encryption requirement function, the system can intelligently adjust the encryption strategy according to the different requirements of the transmitted content, not only enhancing the security of data transmission but also avoiding resource waste caused by unnecessary over-encryption. This flexible encryption mechanism significantly improves the efficiency and security of data transmission, ensuring that different data types can obtain the most suitable protection in different network environments.

[0113] 3. By adaptively adjusting the encryption strength through steps, the problem that traditional static encryption strategies cannot cope with dynamic network condition changes is solved, thereby improving the encryption efficiency and optimizing the network performance. In traditional network encryption schemes, a fixed encryption strength is usually used to protect data transmission. However, the fixed encryption strength cannot adapt to the changes in the network environment, resulting in the fact that when the network condition is poor, too high an encryption strength may affect the transmission efficiency, while when the network condition is good, too low an encryption strength may not effectively protect the data security. Therefore, the system needs to dynamically adjust the encryption strength according to the real-time network condition to ensure the data security and transmission efficiency. In this solution, by obtaining the key parameters of the transmission network - latency, packet loss rate, bandwidth, and path reliability, and combining with the "network state risk assessment function", the network risk level is calculated, and the encryption strength is adjusted adaptively accordingly. This method can flexibly adjust the encryption strategy according to the real-time condition of the network. For example, when the network latency is high and the packet loss rate is large, the system automatically reduces the encryption strength to reduce the impact of encryption operations on the transmission performance; while when the network state is good, the system increases the encryption strength to ensure the data security. Through this mechanism, the system can adjust the encryption strength according to the real-time network state, avoiding the resource waste caused by over-encryption and also avoiding the data leakage risk caused by over-encryption. This dynamic encryption strategy not only improves the efficiency of data transmission but also ensures appropriate security protection under various network conditions, thus optimizing the balance between security and performance in the data transmission process.

[0114] 4. By means of different encryption strategies in the three levels of encryption in Step 3, the problem of being unable to flexibly adjust the encryption level under different network environments and data security requirements is solved, thus effectively balancing the contradiction between encryption strength and transmission efficiency, and enhancing the flexibility and security of data transmission. In traditional encryption schemes, the encryption strength is usually set statically, which means that all transmitted data uses the same encryption level, regardless of the security requirements of the data itself or the differences in network environments. This one-size-fits-all approach often leads to over-encryption in some cases, not only wasting computing resources but also possibly causing delays in network transmission and excessive bandwidth consumption. In other cases, using a lower encryption strength may not provide sufficient protection, resulting in an increased security risk. This solution provides flexible encryption options for different network states and data types by setting three different levels of encryption strategies: high-strength encryption, medium-strength encryption, and low-strength encryption. Specifically, high-strength encryption: When the number of data blocks is large, by using large prime numbers and a higher number of bits, it ensures the maximum security of the transmitted data and is applicable to high-risk transmission scenarios, such as the transmission of sensitive data or high-value data. Medium-strength encryption: Based on the number of data blocks and moderate prime number settings, it is applicable to situations where a balance needs to be found between protecting data security and transmission efficiency. This encryption strategy can ensure good security while avoiding excessive consumption of computing resources in unnecessary situations. Low-strength encryption: For low-risk transmissions, it reduces the complexity of encryption, uses fewer data blocks and lower prime number settings, ensures the efficiency of transmission under poor network conditions, and reduces the burden brought by encryption operations. Through this mechanism of dynamically adjusting the encryption strength, the system can automatically select the appropriate encryption scheme according to actual needs and network conditions, avoiding the resource waste and security risks brought by a fixed encryption strength. This hierarchical encryption method enhances the flexibility of data transmission, ensures that while guaranteeing security, it optimizes transmission efficiency, especially in cases where network latency or bandwidth is limited, and can effectively reduce the impact of encryption on performance.

[0115] 5. Through blockchain-based secure transmission, the credibility problem in the data transmission process is solved, ensuring the integrity and legality of the data, thus enhancing the security and immutability of data transmission. In the traditional data transmission process, the security of data usually depends on a centralized authentication mechanism, which has risks of single-point failure and tampering, and lacks an effective verification mechanism during transmission, making it vulnerable to man-in-the-middle attacks or malicious tampering. These problems make it difficult to guarantee the credibility of data transmission, especially when dealing with sensitive data, where the security requirements are particularly strict. This solution effectively solves the above problems by introducing blockchain technology. Specifically, the creation of blockchain data transmission nodes: Each data transmission generates a new transmission block, which contains encrypted data and a random value. The introduction of the random value ensures the non-repeatability of each data transmission, preventing data from being tampered with or replay attacked. This immutable feature greatly enhances the security of data transmission and ensures the integrity of data during transmission. Smart contracts control data transmission permissions: Through the verification mechanism of smart contracts, the system can ensure that only authorized users can perform data transmission. The random verification algorithm used by smart contracts further improves the legitimacy verification of transmission requests, avoiding the intrusion of illegal users and unauthorized transmission operations. This automated permission control mechanism based on smart contracts reduces the risk of human intervention and improves the overall security of the system. Verification and confirmation after transmission: After the data transmission is completed, the target node verifies the data integrity through an inverse hash function to ensure that the data has not been tampered with during transmission. If the hash values of the transmission blocks are inconsistent, the target node can immediately identify that the data has been tampered with and take corresponding measures. This mechanism enables every step of data transmission to be effectively verified and confirmed, ensuring the immutability and authenticity of the data. By introducing blockchain technology, the entire data transmission process is fully verified and protected, avoiding the single-point failure problem in traditional data transmission methods and enhancing the security and credibility of data transmission. At the same time, based on the verification mechanisms of smart contracts and hash verification, data transmission not only has high security but also can detect any tampering behavior in a timely manner after transmission, greatly improving the transparency and trust in the data transmission process. This blockchain-driven data transmission security solution ensures the integrity, authenticity, and immutability of sensitive data, greatly enhancing the protection ability of the system.

[0116] 6. Through an intelligent management solution with end-to-end encryption, challenges in path selection, encryption policies, and key management during data transmission are addressed, ensuring the security, flexibility, and efficiency of data transmission, thereby enhancing the protection and response capabilities of the entire network. Intelligent selection of transmission paths: Traditional data transmission usually relies on static configuration in path selection, which may lead to inflexible and inefficient selection of data transmission paths and inability to adapt to changes in network conditions in real time. By setting a set of transmission paths and using an optimization function for path selection to calculate the optimal transmission path, this solution solves this problem. Path optimization takes into account factors such as the basic cost of the transmission path, content sensitivity, and security, ensuring that the selected path not only meets performance requirements but also maximally guarantees data security during transmission. Such dynamic path selection improves transmission efficiency and effectively avoids potential network attacks and security risks. Real-time adjustment of encryption policies: As network transmission conditions change, such as latency, bandwidth, packet loss rate, etc., traditional encryption policies often fail to flexibly adapt to the current network environment, resulting in insufficient encryption intensity or excessive waste of computing resources. This solution adjusts the encryption level in real time by dynamically monitoring data based on network transmission, using an encryption level adjustment function to balance encryption intensity and network load, ensuring optimal resource utilization while ensuring data security. The dynamic adjustment of encryption policies enhances flexibility during transmission, being able to increase encryption intensity when network conditions are poor and reduce encryption intensity when the network environment is good to improve transmission efficiency. Key management and update mechanism: Key management is an important link in ensuring the security of encrypted data. Traditional static key management methods have the risk of key leakage, while frequent key updates may increase system complexity. This solution generates new keys by combining the risk of the transmission path and the current timestamp, using a high-randomness large prime number generation function, avoiding the security risks of static keys. The update of keys during each transmission process enhances encryption intensity, ensuring the timeliness and unpredictability of keys, thereby reducing the risk of key leakage. At the same time, the regular update of keys enhances the ability to prevent modern network attacks, such as man-in-the-middle attacks, improving the security of the system. Through the intelligent selection of transmission paths, the dynamic adjustment of real-time encryption policies, and the key management and update mechanism, this solution effectively solves the problems of inflexible path selection, encryption policies, and insecure key management in traditional network encrypted transmission. These innovative management measures not only improve the security and efficiency of data transmission but also enhance the adaptability and response capabilities of the entire system in different network environments, ensuring that data is always effectively protected under complex and changing network conditions.

[0117] 7. Calculate the optimized cost of the transmission path through the basic cost function, which solves the problems of low path selection efficiency and unpredictable transmission quality during network transmission, and ensures the efficiency, stability, and reliability of the data transmission process. Obtain the delay, packet loss rate, and bandwidth of the transmission path: In traditional data transmission, the actual situation of network quality is often ignored when selecting a path, resulting in the selected path may have problems such as high delay and frequent packet loss in some cases, thus affecting the overall transmission performance. This solution provides accurate data support for path selection by obtaining the three key indicators of path delay, packet loss rate, and bandwidth, ensuring a comprehensive understanding of the current network condition. This approach solves the problem of not considering the actual network load when selecting a path. Weighted calculation of the basic cost function: By introducing a weighting coefficient to perform a weighted sum calculation on the delay, packet loss rate, and bandwidth, a comprehensive "basic cost function" is formed. This function can dynamically adjust the path selection preference according to the changes in the network environment, ensuring that the selected path not only considers factors such as delay and bandwidth but also adjusts the weights according to different network environments, enhancing the flexibility and adaptability of path selection. This function solves the problem that traditional static path selection methods cannot adapt to dynamic network environments. Improve the quality and efficiency of transmission path selection: The basic cost function that comprehensively considers network delay, bandwidth, and packet loss rate helps to select the best path among multiple transmission paths. By minimizing the weighted cost, the system can intelligently select a path with low delay, sufficient bandwidth, and low packet loss rate, thus enhancing the efficiency and stability of data transmission. This not only increases the data transmission speed but also reduces the data loss rate caused by unstable transmission, thereby reducing the risks brought by the network. Optimize resource utilization and reduce unnecessary load: During network transmission, selecting a low-cost path can not only speed up data transmission but also optimize the utilization of bandwidth and computing resources, reduce unnecessary load, and improve the overall performance of the system. By accurately calculating the basic cost of each path, it is ensured that the system can automatically optimize the use of resources when selecting a path, enhancing the operation efficiency of the system.

[0118] 8. Quantify the sensitivity of the transmitted content through the content sensitivity function, solve the problem of failing to take appropriate protection measures according to different data types during data transmission, and improve data security and the pertinence of encryption policies. Introduce the content sensitivity function: In traditional data encryption, all data is often regarded as equal, ignoring the differences in privacy and security among different types of data. By setting the content sensitivity function, different encryption and protection policies can be set for different data contents. For example, the sensitivity of personal sensitive information such as ID numbers and bank account numbers is much higher than that of some non-sensitive data. The content sensitivity function flexibly sets the encryption intensity and transmission policy of data according to factors such as data type and privacy requirements to ensure that sensitive data is more tightly protected. This step effectively solves the problem of not setting different security protection measures according to data types. Precisely quantify the sensitivity of the content: By designing a sensitivity evaluation function for different content types, the privacy level, confidentiality level, and risk of leakage of the content can be quantified. This function can dynamically adjust the encryption intensity and protection measures according to the different natures of the content, such as personal information and business secrets, thus avoiding the performance burden caused by excessive encryption. This not only improves the flexibility of data protection but also reduces unnecessary resource waste and enhances the performance of the system. Enhance targeted data protection policies: In the traditional method without a sensitivity function, the encryption intensity of all data is usually unified, which may lead to excessive encryption of some non-sensitive data, increasing the system burden, while sensitive data may be exposed due to insufficient protection. By introducing the content sensitivity function, the system can automatically adjust the encryption policy according to the data type and privacy requirements, thus ensuring that sensitive data is optimally protected while avoiding excessive encryption of low-sensitivity data. This policy effectively improves the security of data transmission and optimizes the use efficiency of computing and bandwidth resources. Improve the efficiency and security of data transmission: By flexibly adjusting the encryption policy according to the sensitivity of the content, the system can maximize the efficiency of data transmission while ensuring data security. Sensitive data will be protected with a higher intensity, while non-sensitive data can adopt appropriate protection measures to avoid unnecessary encryption burdens. This policy optimizes the efficiency of data transmission, enabling the system to improve the overall performance while ensuring security. BRIEF DESCRIPTION OF THE DRAWINGS

[0119] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0120] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0121] Example, referring to Figure 1 , a network information protection method based on big data analysis, including:

[0122] S1. Dynamic transmission channel encryption:

[0123] S11. Establish a transmission channel identification system:

[0124] Obtain the type of the transmission content, denoted as ContentType;

[0125] The types of the transmission content include sensitive content Sensitive, public content Public, and general content General;

[0126] Obtain the source address of the transmission, denoted as Source;

[0127] Obtain the destination address of the transmission, denoted as Destination;

[0128] Obtain the timestamp at the time of transmission, denoted as Timestamp;

[0129] Set a custom generation function, denoted as g, where g is a multi-dimensional mapping function based on ContentType, Source, Destination, and Timestamp, specifically:

[0130]

[0131] Among them, is a mapping function, specifically:

[0132]

[0133] Among them, Hash(·) is a custom hash function that converts the input string into a fixed-length numerical value. The design of this hash function is to combine the mapping methods of numbers and characters, generate values by weighted combination of different types of data sources, and avoid hash collisions, specifically:

[0134] Set a large prime number to ensure the unpredictability of the output value, denoted as P1;

[0135]

[0136] wherein, X i is the ASCII value of the i-th character of the string X; α i is the weight coefficient of the i-th character of the string X, which is set by the system during initialization, considering the frequency and security of the character; n is the total number of characters of the string X; mod is the modulo operation;

[0137] Record the calculation result of the mapping function as the intermediate value V;

[0138] Set the high-dimensional mapping function, specifically:

[0139] Set a large prime number to ensure the randomness and unpredictability of the output value, denoted as P2, and P2 ≠ P1;

[0140]

[0141] wherein, sin(V), cos(V) and log(V + 1) are three mathematical transformations of the intermediate value V respectively, generating non-linear changes;

[0142] Take the calculation result of the high-order mapping function as the unique identifier, denoted as UID;

[0143] S12, real-time analyze the type of transmission content;

[0144] S13, adaptively adjust the encryption strength;

[0145] S2, blockchain-based secure transmission;

[0146] S3, intelligent management of end-to-end encryption.

[0147] By establishing a transmission channel identification system, the problem of unique identification of data such as the type of transmission content, source address, destination address, and timestamp during the transmission process is solved, and more precise encryption protection is provided. Through a custom generation function, combined with the multi-dimensional mapping of the type of transmission content, source address, destination address, and timestamp, a unique transmission channel identifier is generated. This identifier ensures the uniqueness of each transmission channel in the big data environment, enabling each transmission process to obtain precise encryption control. Specifically, by performing weighted mapping on each character of the string through a hash function, the problem of hash collision is avoided, ensuring the uniqueness of the identifier. Combining the use of a high-dimensional mapping function and a large prime number further increases the unpredictability of the output value, enhances the security of encryption, and thus effectively prevents man-in-the-middle attacks and replay attacks.

[0148] The real-time analysis of the type of transmission content specifically includes:

[0149] Based on the type of the transmitted content, an encryption requirement function f(ContentType) is set. This function is designed based on a new model, considering the encryption requirements and complexity of the content, and adopts a linear weighting method, specifically as follows:

[0150]

[0151] Among them, β1, \2, and β3 are the weight coefficients of various types of content; is an indicator function. If the input condition is true, the value is 1; if the input condition is false, the value is 0;

[0152] γ1 represents the encryption requirement weight of Sensitive. For sensitive content, the weight coefficient β1 is larger, indicating that it requires stronger encryption protection. Usually, this value will be set to a relatively high number, such as β1 = 10; β2 represents the encryption requirement weight of Public. For public content, the weight coefficient β2 is smaller, indicating that its encryption requirement is lower. Usually, this value will be set to a relatively small number, such as β2 = 1; β3 represents the encryption requirement weight of General. The encryption requirement of this type of content is between sensitive content and public content, and the weight coefficient β3 can be set to a medium number, such as β3 = 5.

[0153] By analyzing the content type of the transmission in real time through steps, the problem that traditional encryption schemes cannot dynamically adjust the encryption intensity according to different content types is solved, thereby improving the encryption efficiency and the accuracy of data protection. In traditional network information protection, a fixed encryption method is usually used to encrypt all transmitted data. This static encryption method cannot adapt to the security requirements of different data. To address this issue, this solution designs an encryption requirement function based on the content type of the transmission. This function uses a linear weighting method, considering the encryption requirements and complexity of the content, and sets different encryption intensity requirements for different types of content. By setting the weight coefficients, the system can automatically adjust the encryption policy according to the content type, such as sensitive data, public data, and general data, to ensure that highly sensitive data obtains sufficient encryption protection without over-encrypting public data, thereby optimizing the use of encryption resources. During this process, the introduction of the indicator function further improves the flexibility of the encryption requirements, enabling the encryption requirement function to accurately judge the encryption intensity requirements of different transmitted content. For example, for sensitive content, the indicator function will be in the "true" state, triggering a higher encryption intensity; while for public content, the indicator function is in the "false" state, correspondingly reducing the encryption intensity to ensure that the transmission efficiency is not affected. Through the design of this encryption requirement function, the system can intelligently adjust the encryption policy according to the different requirements of the transmitted content, not only enhancing the security of data transmission but also avoiding resource waste caused by unnecessary over-encryption. This flexible encryption mechanism significantly improves the efficiency and security of data transmission, ensuring that different data types can be optimally protected in different network environments.

[0154] The self-adaptive adjustment of the encryption intensity specifically includes:

[0155] Obtain the transmission network latency, denoted as NetworkLatency;

[0156] Obtain the transmission packet loss rate, denoted as PacketLoss;

[0157] Obtain the transmission network bandwidth, denoted as Bandwidth;

[0158] Obtain the reliability of the transmission network path, denoted as Reliability;

[0159] Set a network status risk assessment function, calculate the network status risk level, and adjust the encryption intensity, specifically as follows:

[0160] The network status risk assessment function is:

[0161]

[0162] where γ1, γ2, γ3, and γ4 are network status factors for adjusting the risk assessment;

[0163] Set three levels of encryption strength, namely:

[0164] ψ: High-strength encryption;

[0165] φ: Medium-strength encryption;

[0166] Low-strength encryption;

[0167] Adjust the encryption strength according to the calculation result of the network status risk assessment function:

[0168] Record the calculation result of the network status risk assessment function as R;

[0169]

[0170] where EncryptionStrength is the encryption strength.

[0171] Through the self-adaptive adjustment of the encryption strength in the steps, the problem that the traditional static encryption strategy cannot cope with the dynamic changes of the network situation is solved, thereby improving the encryption efficiency and optimizing the network performance. In the traditional network encryption scheme, a fixed encryption strength is usually used to protect data transmission. However, the fixed encryption strength cannot adapt to the changes in the network environment, resulting in that when the network condition is poor, too high encryption strength may affect the transmission efficiency, and when the network condition is good, too low encryption strength may not effectively protect the security of the data. Therefore, the system needs to dynamically adjust the encryption strength according to the real-time network situation to ensure the security and transmission efficiency of the data. In this solution, by obtaining the key parameters of the transmission network - delay, packet loss rate, bandwidth, and path reliability, combined with the "network status risk assessment function", calculate the network risk level, and accordingly adjust the encryption strength adaptively. This method can flexibly adjust the encryption strategy according to the real-time situation of the network. For example, when the network delay is high and the packet loss rate is large, the system automatically reduces the encryption strength to reduce the impact of encryption operations on the transmission performance; while when the network status is good, the system increases the encryption strength to ensure the security of the data. Through this mechanism, the system can adjust the encryption strength according to the real-time network status, avoiding the waste of resources caused by over-encryption and also avoiding the risk of data leakage caused by over-encryption. This dynamic encryption strategy not only improves the efficiency of data transmission but also ensures that appropriate security protection can be provided under various network conditions, thus optimizing the balance between security and performance in the data transmission process.

[0172] The three levels of encryption strength specifically include:

[0173] The high-strength encryption ψ is specifically:

[0174] Set a large prime number, denoted as P3, and P3≠P2;

[0175] Obtain the total number of data blocks during transmission, denoted as ψ n ;

[0176]

[0177] Among them, k i is the weight coefficient of the i-th data block; DataBit i is the number of bits of the i-th data block; k i is the weight coefficient of the i-th data block, reflecting the complexity of different data blocks;

[0178] The medium-strength encryption φ is specifically as follows:

[0179] Set a large prime number, denoted as P4, and P4 ≠ P3;

[0180] Set the number of data blocks required for medium encryption, denoted as φ n ;

[0181]

[0182] Low-strength encryption is specifically as follows:

[0183] Set a large prime number, denoted as P5, and P5 ≠ P4;

[0184] Set the minimum number of data blocks required for low-strength encryption, denoted as

[0185]

[0186] By means of different encryption strategies in the three-level encryption in Step 3, the problem of being unable to flexibly adjust the encryption level under different network environments and data security requirements is solved, thus effectively balancing the contradiction between encryption intensity and transmission efficiency, and enhancing the flexibility and security of data transmission. In traditional encryption schemes, the encryption intensity is usually set statically, which means that all transmitted data uses the same encryption level regardless of the security requirements of the data itself or the differences in network environments. This one-size-fits-all approach often leads to over-encryption in some cases, not only wasting computing resources but also potentially causing delays in network transmission and excessive bandwidth consumption. In other cases, using a lower encryption intensity may not provide sufficient protection, resulting in an increased security risk. This solution provides flexible encryption options for different network states and data types by setting three different levels of encryption strategies: high-intensity encryption, medium-intensity encryption, and low-intensity encryption. Specifically, high-intensity encryption: When the number of data blocks is large, by using large prime numbers and a higher number of bits, it ensures the maximum security of the transmitted data and is applicable to high-risk transmission scenarios such as the transmission of sensitive data or high-value data. Medium-intensity encryption: Based on the number of data blocks and moderate prime number settings, it is applicable to situations where a balance needs to be found between protecting data security and transmission efficiency. This encryption strategy can ensure good security while avoiding excessive consumption of computing resources in unnecessary situations. Low-intensity encryption: For low-risk transmissions, it reduces the encryption complexity, uses fewer data blocks and lower prime number settings to ensure high efficiency in transmission under poor network conditions and reduces the burden brought by encryption operations. Through this mechanism of dynamically adjusting the encryption intensity, the system can automatically select the appropriate encryption scheme according to actual needs and network conditions, avoiding the resource waste and security risks brought by a fixed encryption intensity. This hierarchical encryption method enhances the flexibility of data transmission, ensures security while optimizing transmission efficiency, especially in cases where network latency or bandwidth is limited, and can effectively reduce the impact of encryption on performance.

[0187] The blockchain-based secure transmission specifically includes:

[0188] The blockchain is an existing technology;

[0189] S21. Create a blockchain data transmission node:

[0190] Each time data is transmitted, a transmission block is generated, denoted as B, which contains the following content:

[0191] B = (UID, EncryptedData, Timestamp, Source, Destination, Nonce);

[0192] Among them, EncryptedData is the encrypted data; Nonce is a random value to ensure the non-repeatability during data transmission;

[0193] S22. The smart contract controls the data transmission permission:

[0194] Obtain the user credentials, denoted as UserCredentials;

[0195] Set a random verification algorithm and perform the transmission verification V(UID, UserCredentials), specifically:

[0196] Set a large prime number, denoted as P6, and P6 ≠ P5;

[0197] V(UID, UserCredentials) = (h(UID, UserCredentials, Timestamp)) mod P6;

[0198] Among them, h(·) is a hash function;

[0199] If the result of the random verification algorithm V(UID, UsserCredentials) is zero, the transmission is allowed;

[0200] If the result of the random verification algorithm V(UID, UserCredentials) is not zero, the transmission is allowed;

[0201] S23. Verification and confirmation after transmission:

[0202] When verifying the integrity of the block transmission, perform the verification through the reverse hash function:

[0203]

[0204] Among them, h(B) and h(B') are the hash values of the transmitted blocks respectively. If the two are equal, it is determined that the data has not been tampered with. If the two are not equal, it is determined that the data has been tampered with; B' is the block received by the target node. After receiving the data, the target node will check according to the content in B and the hash value from the source node to ensure that the data has not been tampered with.

[0205] Through the blockchain-based secure transmission steps, the credibility problem in the data transmission process is solved, ensuring the integrity and legality of the data, thus enhancing the security and immutability of the data transmission. In the traditional data transmission process, the security of the data usually depends on the centralized authentication mechanism, which has the risks of single-point failure and tampering, and lacks an effective verification mechanism during the transmission process, making it vulnerable to man-in-the-middle attacks or malicious tampering. These problems make it difficult to guarantee the credibility of data transmission, especially when facing sensitive data, the security requirements are particularly strict. This solution effectively solves the above problems by introducing blockchain technology. Specifically, the creation of blockchain data transmission nodes: Each data transmission generates a new transmission block, which contains the encrypted data and a random value. The introduction of the random value ensures the non-repeatability of each data transmission, preventing data from being tampered with or replay attacked. This immutable feature greatly enhances the security of data transmission and ensures the integrity of the data during the transmission process. Smart contracts control data transmission permissions: Through the verification mechanism of smart contracts, the system can ensure that only authorized users can perform data transmission. The random verification algorithm used by smart contracts further improves the legitimacy verification of transmission requests, avoiding the intrusion of illegal users and unauthorized transmission operations. This automated permission control mechanism based on smart contracts reduces the risk of human intervention and improves the overall security of the system. Verification and confirmation after transmission: After the data transmission is completed, the target node checks the data integrity through the reverse hash function to ensure that the data has not been tampered with during the transmission process. If the hash values of the transmission blocks are inconsistent, the target node can immediately identify that the data has been tampered with and take corresponding measures. This mechanism enables every step of the data transmission to be effectively verified and confirmed, ensuring the immutability, authenticity, and reliability of the data. By introducing blockchain technology, the entire data transmission process is fully verified and protected, avoiding the single-point failure problem in the traditional data transmission method, and enhancing the security and credibility of data transmission. At the same time, based on the verification mechanisms of smart contracts and hash verification, the data transmission not only has high security but also can detect any tampering behavior in a timely manner after the transmission is completed, greatly improving the transparency and trust in the data transmission process. This blockchain-driven data transmission security solution ensures the integrity, authenticity, and immutability of sensitive data, greatly enhancing the protection ability of the system.

[0206] The intelligent management of end-to-end encryption specifically includes:

[0207] S31. Intelligent selection of transmission path:

[0208] Set a set of transmission paths, denoted as Paths;

[0209] Obtain all the transmission paths and add them to the transmission path set Paths;

[0210] Based on the path selection optimization function P(ContentType), calculate the optimal transmission path:

[0211]

[0212] Among them, is the basic cost function of the transmission path p; is the content sensitivity function of the transmission path p, considering the encryption requirements of the content, the wind direction weight, and the security of the path;

[0213] S32. Real-time encryption policy adjustment:

[0214] Based on the network transmission dynamic monitoring data, set the encryption level adjustment function, specifically:

[0215] A(NetworkStatus, ContentType) = R(NetworkStatus)·δ1 + f(ContentType)·δ2;

[0216] Among them, δ1 and δ2 are the weight coefficients of the encryption strength; A(NetworkStatus, ContentType) is used to adjust the encryption strength;

[0217] S33. Key management and update mechanism:

[0218] Obtain the current timestamp, denoted as Timestamp current ;

[0219] Obtain the currently used encryption key, denoted as K old ;

[0220] Obtain the risk score of the transmission path, denoted as PathRisk;

[0221] Set a large prime number, denoted as P7, to ensure that the generated key has high randomness and security, and P7 ≠ P6;

[0222] Generate a new key by combining the transmission path risk and the current timestamp. The key update function is specifically:

[0223]

[0224] Through an intelligent management solution with end-to-end encryption, challenges in path selection, encryption strategy, and key management during data transmission are addressed, ensuring the security, flexibility, and efficiency of data transmission, thereby enhancing the protection and response capabilities of the entire network. Intelligent selection of transmission paths: Traditional data transmission usually relies on static configuration in path selection, which may lead to inflexible and inefficient selection of data transmission paths and inability to adapt to changes in network conditions in real time. By setting a set of transmission paths and using an optimization function for path selection to calculate the optimal transmission path, this solution solves this problem. Path optimization takes into account factors such as the basic cost of the transmission path, content sensitivity, and security, ensuring that the selected path not only meets performance requirements but also maximally guarantees data security during transmission. Such dynamic path selection improves transmission efficiency and effectively avoids potential network attacks and security risks. Real-time adjustment of encryption strategy: As network transmission conditions change, such as latency, bandwidth, packet loss rate, etc., traditional encryption strategies often fail to flexibly adapt to the current network environment, resulting in insufficient encryption intensity or excessive waste of computing resources. This solution adjusts the encryption level in real time by dynamically monitoring data based on network transmission, using an encryption level adjustment function to balance encryption intensity and network load, ensuring optimal resource utilization while ensuring data security. The dynamic adjustment of the encryption strategy enhances flexibility during transmission, increasing encryption intensity when network conditions are poor and decreasing encryption intensity when the network environment is good to improve transmission efficiency. Key management and update mechanism: Key management is an important link to ensure the security of encrypted data. Traditional static key management methods have the risk of key leakage, while frequent key updates may increase system complexity. This solution generates new keys by combining the risk of the transmission path and the current timestamp, using a high-randomness large prime number generation function, avoiding the security risks of static keys. The update of keys during each transmission process enhances encryption intensity, ensuring the timeliness and unpredictability of keys, thereby reducing the risk of key leakage. At the same time, the regular update of keys enhances the ability to prevent modern network attacks such as man-in-the-middle attacks, improving the security of the system. Through the intelligent selection of transmission paths, the dynamic adjustment of real-time encryption strategies, and the key management and update mechanism, this solution effectively solves the problems of inflexible path selection, encryption strategy, and insecure key management in traditional network encryption transmission. These innovative management measures not only improve the security and efficiency of data transmission but also enhance the adaptability and response capabilities of the entire system in different network environments, ensuring that data is always effectively protected under complex and changing network conditions.

[0225] The said basic cost function specifically includes:

[0226] Obtain the latency of transmission path p, denoted as Latency(p);

[0227] Obtain the packet loss rate of the transmission path p, denoted as PacketLoss(p);

[0228] Obtain the bandwidth of the transmission path p, denoted as Bandwidth(p);

[0229] The basic cost function is specifically as follows:

[0230]

[0231] Among them, λ1, λ2, and λ3 are the weighting coefficients of each factor.

[0232] Calculate the optimization cost of the transmission path through the basic cost function, which solves the problems of low path selection efficiency and unpredictable transmission quality during network transmission, and ensures the efficiency, stability, and reliability of the data transmission process. Obtain the delay, packet loss rate, and bandwidth of the transmission path: In traditional data transmission, the actual situation of network quality is often ignored when selecting a path, resulting in the selected path may have problems such as high delay and frequent packet loss in some cases, thus affecting the overall transmission performance. This solution provides accurate data support for path selection by obtaining three key indicators of path delay, packet loss rate, and bandwidth, ensuring a comprehensive understanding of the current network conditions. This approach solves the problem of not considering the actual network load when selecting a path. Weighted calculation of the basic cost function: By introducing weighting coefficients to perform weighted summation calculations on delay, packet loss rate, and bandwidth, a comprehensive "basic cost function" is formed. This function can dynamically adjust the path selection preference according to changes in the network environment, ensuring that the selected path not only considers factors such as delay and bandwidth, but also adjusts the weights according to different network environments, improving the flexibility and adaptability of path selection. This function solves the problem that traditional static path selection methods cannot adapt to dynamic network environments. Improve the quality and efficiency of transmission path selection: The basic cost function that comprehensively considers network delay, bandwidth, and packet loss rate helps to select the best path among multiple transmission paths. By minimizing the weighted cost, the system can intelligently select a path with low delay, sufficient bandwidth, and low packet loss rate, thereby improving the efficiency and stability of data transmission. This not only increases the data transmission speed, but also reduces the data loss rate caused by unstable transmission, thus reducing the risks brought by the network. Optimize resource utilization and reduce unnecessary load: During network transmission, selecting a low-cost path can not only speed up data transmission, but also optimize the utilization of bandwidth and computing resources, reduce unnecessary load, and improve the overall performance of the system. By accurately calculating the basic cost of each path, it is ensured that the system can automatically optimize the use of resources when selecting a path, improving the operation efficiency of the system.

[0233] The content sensitivity function specifically includes:

[0234]

[0235] Quantify the sensitivity of the transmitted content through a content sensitivity function, solve the problem that appropriate protection measures are not taken according to different data types during data transmission, and improve the data security and the pertinence of encryption strategies. Introduce the content sensitivity function: In traditional data encryption, all data is often regarded as equivalent, ignoring the differences in privacy and security among different types of data. By setting the content sensitivity function, different encryption and protection strategies can be set for different data contents. For example, the sensitivity of personal sensitive information such as ID numbers and bank account numbers is much higher than that of some non-sensitive data. The content sensitivity function flexibly sets the encryption intensity and transmission strategy of the data according to factors such as data type and privacy requirements to ensure that sensitive data is more tightly protected. This step effectively solves the problem of not setting different security protection measures according to data types. Precisely quantify the sensitivity of the content: By designing a sensitivity evaluation function for different content types, the privacy level, confidentiality level, and risk of leakage of the content can be quantified. This function can dynamically adjust the encryption intensity and protection measures according to the different natures of the content, such as personal information and trade secrets, so as to avoid the performance burden caused by over-encryption. This not only improves the flexibility of data protection, but also reduces unnecessary resource waste and improves the performance of the system. Enhance targeted data protection strategies: In the traditional method without a sensitivity function, the encryption intensity of all data is usually unified, which may lead to over-encryption of some non-sensitive data, increasing the system burden, while sensitive data may be exposed due to insufficient protection. By introducing the content sensitivity function, the system can automatically adjust the encryption strategy according to the data type and privacy requirements, so as to ensure that sensitive data is optimally protected while avoiding over-encryption of low-sensitivity data. This strategy effectively improves the security of data transmission and optimizes the use efficiency of computing and bandwidth resources. Improve the efficiency and security of data transmission: By flexibly adjusting the encryption strategy according to the sensitivity of the content, the system can maximize the efficiency of data transmission on the premise of ensuring data security. Sensitive data will be protected with a higher intensity, while non-sensitive data can adopt appropriate protection measures to avoid unnecessary encryption burden. This strategy optimizes the efficiency of data transmission, enabling the system to improve the overall performance while ensuring security.

[0236] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0237] The above are only the preferred embodiments of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A network information protection method based on big data analysis, characterized in that: include: S1. Dynamic transmission channel encryption: S11. Establish a transmission channel identification system: Get the type of the transmitted content, recorded as ContentType; The types of the transmitted content include sensitive content, public content and general content; Get the source address of the transmission, recorded as Source; Get the destination address of the transmission, recorded as Destination; Get the timestamp of transmission, recorded as Timestamp; Set a custom generation function, denoted as g, which is a multidimensional mapping function based on ContentType, Source, Destination, and Timestamp. Specifically: in, is the mapping function, specifically: Hash(·) is a custom hash function that converts the input string into a fixed-length numeric value, specifically: Set a large prime number, denoted as P1; Among them, X i is the ASCII value of the i-th character in string X; α i is the weight coefficient of the i-th character in string X; n is the total number of characters in string X; mod is the modulus operation; The calculation result of the mapping function is recorded as the intermediate value V; Set the high-dimensional mapping function, specifically: Set a large prime number, denoted as P2, and P2≠P1; Among them, sin(V), cos(V) and log(V+1) are three mathematical transformations of the intermediate value V, which produce nonlinear changes; The result calculated by the high-order mapping function is used as a unique identifier, recorded as UID; S12, analyzing the transmission content type in real time; S13, adaptive adjustment of encryption strength; S2, secure transmission based on blockchain; S3, intelligent management of end-to-end encryption.

2. According to the network information protection method based on big data analysis according to claim 1, it is characterized in that: The real-time analysis of the transmission content type specifically includes: Based on the type of transmitted content, an encryption requirement function f(ContentType) is set. This function uses a linear weighted method, specifically: Among them, β1, β2 and β3 are the weight coefficients of each type of content; It is an indicator function. If the input condition is true, the value is 1, and if the input condition is false, the value is 0.

3. According to the network information protection method based on big data analysis according to claim 2, it is characterized in that: The encryption strength adaptive adjustment specifically includes: Get the transmission network delay, recorded as NetworkLatency; Get the transmission packet loss rate, denoted as PacketLoss; Get the transmission network bandwidth, recorded as Bandwidth; Get the reliability of the transmission network path, denoted as Reliability; Set the network status risk assessment function to calculate the network status risk level and adjust the encryption strength, specifically: The network status risk assessment function is: Among them, γ1, γ2, γ3 and γ4 are network status factors that adjust the risk assessment; Set three encryption strengths: ψ: high-strength encryption; φ: medium-strength encryption; Low-strength encryption; Adjust the encryption strength based on the calculation results of the network status risk assessment function: The result of network status risk assessment function calculation is recorded as R; Among them, EncryptionStrength is the encryption strength.

4. A network information protection method based on big data analysis according to claim 3, characterized in that: The three levels of encryption specifically include: High-strength encryption ψ is specifically: Set a large prime number, denoted as P3, and P3≠P2; Get the total number of data blocks during transmission, denoted as ψ n ; Among them, DataBit i is the number of bits of the i-th data block; k i is the weight coefficient of the i-th data block; Medium strength encryption φ is as follows: Set a large prime number, denoted as P4, and P4≠P3; Set the number of data blocks required for medium encryption, denoted as φ n ; Low-strength encryption Specifically: Set a large prime number, denoted as P5, and P5≠P4; Set the minimum number of data blocks required for low-strength encryption, denoted as 5. A network information protection method based on big data analysis according to claim 4, characterized in that: The secure transmission based on blockchain specifically includes: S21. Create a blockchain data transmission node: Each time data is transmitted, a transmission block is generated, denoted as B, which contains the following contents: B=(UID,EncryptedData,Timestamp,Source,Destination,Nonce); Among them, EncryptedData is the encrypted data; Noce is a random value to ensure the non-repeatability of the data transmission process; S22. Smart contract controls data transmission permissions: Get user credentials, recorded as userCredentials; Set the random verification algorithm and perform transmission verification V(UID,UserCredentials), specifically: Set a large prime number, denoted as P6, and P6≠P5; V(UID,UserCredentials=h(UID,UserCredentials,Timestamp))6; Where h(·) is a hash function; If the result of the random verification algorithm V(UID, UserCredentials) is zero, the transmission is allowed; If the result of the random verification algorithm V(UID, UserCredentials) is not zero, the transmission is allowed; S23. Verification and confirmation after transmission is completed: When verifying the integrity of block transmission, check it through the reverse hash function: Among them, h(B) and h(B') are the hash values ​​of the transmitted blocks respectively. If the two are equal, it is determined that the data has not been tampered with. If the two are not equal, it is determined that the data has been tampered with; B' is the block received by the target node.

6. A network information protection method based on big data analysis according to claim 5, characterized in that: The intelligent management of end-to-end encryption specifically includes: S31, intelligent selection of transmission path: Set the transmission path set, denoted as Paths; Get all transmission paths and add them to the transmission path collection Paths; Based on the path selection optimization function P(ContentType), the optimal transmission path is calculated: in, is the basic cost function of the transmission path p; is the content sensitivity function of transmission path p; S32, real-time encryption policy adjustment: Based on the dynamic monitoring data transmitted over the network, set the encryption level adjustment function, specifically: A(NetworkStatus,ContenType)=R(NetworkStatus)·δ1+f(ContentType)·δ2; Among them, δ1 and δ2 are weight coefficients of encryption strength; A(NetworkStatus,ContentType) is used to adjust encryption strength; S33, key management and update mechanism: Get the current timestamp, recorded as Timestamp current ; Get the currently used encryption key, denoted as K old ; Get the risk score of the transmission path, denoted as PathRisk; Set a large prime number, denoted as P7, and P7≠P6; A new key is generated by combining the transmission path risk and the current timestamp. The key update function is as follows:

7. A network information protection method based on big data analysis according to claim 6, characterized in that: The basic cost function specifically includes: Get the delay of transmission path p, denoted as Latency(p); Get the packet loss rate of transmission path p, denoted as PacketLoss(p); Get the bandwidth of the transmission path p, denoted as Bandwidth(p); The basic cost function is specifically: Among them, λ1, λ2 and λ3 are weighted coefficients of each factor.

8. A network information protection method based on big data analysis according to claim 6, characterized in that: The content sensitivity function specifically includes:

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