A network information content encryption method, system and storage medium

Abstract

The present invention discloses a network information content encryption method, system and storage medium, the method comprising: obtaining network data in network traffic in real time and performing data preprocessing to obtain preprocessed network information data; calculating a single character value according to the network information data and obtaining an encrypted character set; constructing an encryption matrix of the network information data according to the network information data and the encrypted character set to obtain an encryption matrix of the network information data; classifying data according to the network information data by preset network information data importance sensitivity to obtain network information classification data; performing data relationship analysis according to the encryption matrix and the network information classification data to obtain an encryption importance matrix; encrypting and transmitting data according to the network information data and the encryption importance matrix. The method can realize flexible classification encryption according to the importance and sensitivity of network information data.

Description

Technical Field

[0001] The present invention relates to the technical field of information encryption, and in particular to a network information content encryption method, system and storage medium. Background Art

[0002] With the rapid development of Internet technology, the scale and diversity of network information content have exploded. Network information transmission faces a variety of security threats, including data leakage, unauthorized access, malicious attacks and other issues. Therefore, how to ensure the security of network information content during transmission and protect sensitive data from being leaked has become an important demand that needs to be urgently addressed in the current network security field. At the same time, since different types of network information have different importance and sensitivity, the requirements for information security protection are also different, which requires considering the differences in data during the encryption process.

[0003] In order to meet the above needs, the existing technology mainly uses data encryption technology to protect network information security. Traditional encryption methods convert the original information into ciphertext by encoding the data, so that unauthorized users cannot obtain the real content of the data. Common encryption technologies include symmetric encryption and asymmetric encryption, which can protect data security and prevent information leakage to a certain extent. At the same time, the security of network information is further enhanced by establishing a secure transmission channel and setting access rights.

[0004] In summary, traditional encryption methods use a unified encryption algorithm to process all data. The encryption process lacks flexibility and pertinence, resulting in a waste of encryption resources. Summary of the invention

[0005] The present invention provides a network information content encryption method, system and storage medium to achieve flexible classification encryption according to the importance and sensitivity of network information data.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides a method for encrypting network information content, comprising:

[0007] Get network data from network traffic in real time;

[0008] Performing data preprocessing according to the network data to obtain preprocessed network information data;

[0009] Calculating a single character value according to the network information data, and obtaining an encrypted character set according to the single character value;

[0010] According to the network information data and the encryption character set, an encryption matrix of the network information data is constructed to obtain an encryption matrix of the network information data;

[0011] According to the network information data, data classification is performed according to preset network information data importance sensitivity to obtain network information classification data;

[0012] Performing data relationship analysis based on the encryption matrix and the network information classification data to obtain an encryption importance matrix;

[0013] According to the network information data and the encryption importance matrix, data encryption is performed and transmitted to achieve secure transmission of the network information data.

[0014] As an optional implementation manner, performing data preprocessing according to the network data to obtain preprocessed network information data includes:

[0015] According to the network information data, decoding and framing preprocessing are performed to obtain network decoded data;

[0016] Extracting features based on the network decoding data to obtain content features;

[0017] Generate a feature vector according to the content feature to obtain a network feature vector;

[0018] According to the feature vector, quantitative scoring is performed to obtain pre-processed network information data;

[0019] The content features include data length, keywords, special characters, sensitive words and multimedia features.

[0020] As an optional implementation manner, the calculating a single character value according to the network information data, and obtaining an encrypted character set according to the single character value, includes:

[0021] The value of a single character is calculated using the following formula:

[0022]

[0023] Perform a character mapping operation according to the single character value to obtain an encrypted character set;

[0024] in, is the sensitivity coefficient; is the importance variable coefficient; is the random number variable coefficient; Variable coefficient for data type; The variable coefficient for the data format; is the index value of data sensitivity and importance; Index value for data type and data format; A single character value representing the encrypted output; It is the multiplier constant used for encryption, which is used to control the magnification or reduction effect during the encryption process.

[0025] As an optional implementation manner, constructing an encryption matrix of the network information data according to the network information data and the encryption character set to obtain the encryption matrix of the network information data includes:

[0026] Calculate the sensitivity and importance of the network information data according to the network information data and the encrypted character set, and obtain the sensitivity variable coefficient and the importance variable coefficient in the encrypted character set;

[0027] According to the network information data and the encryption character set, a data type analysis of the network information data is performed to obtain a data type variable coefficient and a data format variable coefficient in the encryption character set;

[0028] According to the network information data and the encryption character set, random number variable coefficients are randomly generated to obtain random number variable coefficients in the encryption character set;

[0029] An encryption matrix is ​​generated according to the network information data, the encryption character set, the sensitivity variable coefficient, the importance variable coefficient, the data type variable coefficient, the data format variable coefficient and the random number variable coefficient to obtain the encryption matrix of the network information data.

[0030] As an optional implementation manner, the encryption matrix is ​​generated according to the network information data, the encryption character set, the sensitivity variable coefficient, the importance variable coefficient, the data type variable coefficient, the data format variable coefficient and the random number variable coefficient to obtain the encryption matrix of the network information data, including:

[0031] Generate an m×n data matrix according to the network information data and the encryption character set to obtain an initial encryption matrix;

[0032] According to the initial encryption matrix, the sensitivity variable coefficient and the importance variable coefficient are assigned a value to obtain a sensitivity importance matrix;

[0033] According to the sensitivity importance matrix, the data type variable coefficient and the data format variable coefficient are assigned a value to obtain a data feature matrix;

[0034] According to the data feature matrix, the random number variable coefficients are assigned values ​​to obtain an encryption transformation matrix;

[0035] According to the encryption transformation matrix, the parameters in the encryption character set are matrixed to obtain the final encryption matrix of the network information data.

[0036] As an optional implementation manner, the network information data is classified according to a preset network information data importance sensitivity to obtain network information classification data, including:

[0037] Perform sensitivity analysis based on the network information data to obtain sensitivity data;

[0038] Performing importance analysis based on the network information data to obtain importance data;

[0039] According to the sensitivity data and the importance data, encryption strategies for different types of data are determined to obtain network information classification data.

[0040] As an optional implementation, the calculation formulas for the sensitivity analysis and the importance analysis are as follows:

[0041] The calculation formula for sensitivity analysis is:

[0042]

[0043] in, is the sensitive information ratio factor; Sensitive information data; It is non-sensitive information data; is the initial value; The data is sensitive;

[0044] The calculation formula for importance analysis is:

[0045]

[0046] in, is the adjustment factor; is the initial important information length; The number of data partitions for network information; is the initial value; Importance data.

[0047] As an optional implementation manner, performing data relationship analysis based on the encryption matrix and the network information classification data to obtain an encryption importance matrix includes:

[0048] Perform data comparison and analysis based on the encryption matrix and the network information classification data to obtain matrix difference data;

[0049] Perform information encryption matching according to the matrix difference data to obtain an encrypted matching result;

[0050] According to the encrypted matching result, construct a data matrix having a matrix difference length to obtain a second data matrix;

[0051] According to the second data matrix, an inverse matrix is ​​generated by matrix operation to obtain data corresponding to the matrix;

[0052] A matrix construction operation is performed according to the matrix corresponding data to obtain an encrypted importance matrix.

[0053] In a second aspect, the present invention provides a network information content encryption system, comprising:

[0054] A data acquisition module is used to acquire network data in network traffic in real time;

[0055] A data preprocessing module, used to perform data preprocessing according to the network data to obtain preprocessed network information data;

[0056] An encryption character module, used for calculating a single character value according to the network information data, and obtaining an encryption character set according to the single character value;

[0057] An encryption matrix module, used to construct an encryption matrix of the network information data according to the network information data and the encryption character set, to obtain an encryption matrix of the network information data;

[0058] An information classification module, used to classify the network information data according to the preset network information data importance sensitivity to obtain network information classification data;

[0059] An importance module, used to perform data relationship analysis based on the encryption matrix and the network information classification data to obtain an encryption importance matrix;

[0060] The encryption module is used to encrypt and transmit the data according to the network information data and the encryption importance matrix to achieve secure transmission of the network information data.

[0061] In a third aspect, the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the network information content encryption methods described above.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] The present invention provides a network information content encryption method, comprising: acquiring network data in network traffic in real time; performing data preprocessing according to the network data to obtain preprocessed network information data; calculating a single character value according to the network information data, and obtaining an encrypted character set according to the single character value; constructing an encryption matrix of the network information data according to the network information data and the encrypted character set to obtain an encryption matrix of the network information data; performing data classification according to the network information data by preset network information data importance sensitivity to obtain network information classification data; performing data relationship analysis according to the encryption matrix and the network information classification data to obtain an encryption importance matrix; performing data encryption and transmission according to the network information data and the encryption importance matrix to achieve secure transmission of the network information data.

[0064] In the present invention, network data in network traffic is obtained in real time, and the network data is preprocessed to obtain preprocessed network information data, then an encryption character set is constructed to construct an encryption matrix for the network information data, and then data classification is performed according to the preset network information data importance sensitivity to obtain network information classification data, and then data relationship analysis is performed to obtain an encryption importance matrix, and finally data encryption and transmission are performed according to the encryption importance matrix. Among them, the encryption character set realizes the quantitative characterization of the differences in network information data by introducing multiple parameters such as sensitivity variable coefficient, importance variable coefficient, data type variable coefficient, etc., and can perform differential encryption according to the importance and sensitivity of the data. In the encryption process, the encryption matrix and the encryption importance matrix are used simultaneously to encrypt the data, which not only ensures the security of important sensitive data, but also avoids excessive encryption of ordinary data. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a flowchart of a method for encrypting network information content provided by an embodiment of the present invention;

[0066] Figure 2 It is a schematic diagram of the structure of a network information content encryption system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] With the rapid development of Internet technology, the scale and diversity of network information content have exploded. Network information transmission faces a variety of security threats, including data leakage, unauthorized access, malicious attacks and other issues. Therefore, how to ensure the security of network information content during transmission and protect sensitive data from being leaked has become an important demand that needs to be urgently addressed in the current network security field. At the same time, since different types of network information have different importance and sensitivity, the requirements for information security protection are also different, which requires considering the differences in data during the encryption process.

[0068] In order to meet the above needs, the existing technology mainly uses data encryption technology to protect network information security. Traditional encryption methods convert the original information into ciphertext by encoding the data, so that unauthorized users cannot obtain the real content of the data. Common encryption technologies include symmetric encryption and asymmetric encryption, which can protect data security and prevent information leakage to a certain extent. At the same time, the security of network information is further enhanced by establishing a secure transmission channel and setting access rights.

[0069] In summary, traditional encryption methods use a unified encryption algorithm to process all data. The encryption process lacks flexibility and pertinence, resulting in a waste of encryption resources.

[0070] The present invention provides a network information content encryption method, system and storage medium to achieve flexible classification encryption according to the importance and sensitivity of network information data.

[0071] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] Reference Figure 1 The first embodiment of the present invention provides a method for encrypting network information content, comprising the following steps:

[0073] S11, obtaining network data in network traffic in real time;

[0074] S12, performing data preprocessing according to the network data to obtain preprocessed network information data;

[0075] S13, calculating a single character value according to the network information data, and obtaining an encrypted character set according to the single character value;

[0076] S14, constructing an encryption matrix of the network information data according to the network information data and the encryption character set to obtain an encryption matrix of the network information data;

[0077] S15, classifying the network information data according to the preset network information data importance sensitivity to obtain network information classification data;

[0078] S16, performing data relationship analysis according to the encryption matrix and the network information classification data to obtain an encryption importance matrix;

[0079] S17, encrypting and transmitting the data according to the network information data and the encryption importance matrix to achieve secure transmission of the network information data.

[0080] In step S11, network data in network traffic is acquired in real time.

[0081] It should be noted that the network information data described in the present invention includes but is not limited to the following types: text data, image data, audio and video data, compressed file data, etc. By collecting various types of data in network traffic in real time, it can be ensured that the subsequent data preprocessing and encryption process can cover different types of data, thereby providing a comprehensive data protection mechanism. In addition, the frequency of real-time data acquisition can be dynamically adjusted according to the actual network traffic and system processing capacity to achieve the optimal balance between data collection and system performance.

[0082] In step S12, data preprocessing is performed according to the network data to obtain preprocessed network information data, including:

[0083] According to the network information data, decoding and framing preprocessing are performed to obtain network decoded data;

[0084] Extracting features based on the network decoding data to obtain content features;

[0085] Generate a feature vector according to the content feature to obtain a network feature vector;

[0086] According to the feature vector, quantitative scoring is performed to obtain pre-processed network information data;

[0087] The content features include data length, keywords, special characters, sensitive words and multimedia features.

[0088] It should be noted that data length refers to the number of bytes or total number of frames of network information data, which is used to measure the size of data packets. This feature comes from the original network information data. By analyzing the total length of the data, the complexity and content of the data can be roughly evaluated. In network information security detection, the data length feature can help identify abnormal large data packets and avoid possible network attacks or abnormal transmission. Keywords refer to specific words or phrases contained in network information data, which are used to identify the subject or type of data content. These keywords are usually identified by a preset dictionary or keyword list, and are derived from the content of the network information data itself. In the present invention, the keyword feature is used to locate important information or sensitive content, which helps to quickly identify communication data packets involving sensitive data. Special characters refer to non-alphanumeric characters (such as symbols, separators, etc.) that appear in the data, which are used to analyze the structure and format of the data. This feature is obtained by parsing the character composition in the data and is derived from the text content of the network information data. Special character features can help identify different types of data packet formats and play an auxiliary role in data classification. Sensitive words refer to words contained in the data content that may involve privacy, sensitive information or confidential content. These sensitive words are usually matched by a preset sensitive word library and are derived from the content text of the network information data. Sensitive word features are mainly used for security detection to help identify possible security risks and sensitive information transmission. Multimedia refers to non-text content contained in data, such as images, audio, video, etc., which can characterize the multimedia attributes of data. This feature is determined by analyzing the format identifier or content type of the data, and is derived from the encoding and data type tag of the network information data. In information encryption and classification, multimedia features help to determine the specific type of data so that targeted processing methods can be adopted. In the present invention, the extraction and use of the above features can ensure that the classification and encryption process of network information data is more efficient and accurate. The extraction of each feature lays the foundation for the subsequent generation of feature vectors and quantitative scoring, thereby ensuring the security of the encryption process and the data protection effect.

[0089] Among them, it is worth noting that the decoding and framing preprocessing operation refers to decoding the original network information data, restoring the data from a compressed or encrypted state to an analyzable original data format, and framing the data for frame-by-frame analysis. The core of this operation is to decompose the data into individual frames, so that the accuracy of subsequent feature extraction is higher. Exemplarily, in an embodiment of the present invention, the decoding and framing preprocessing operation first restores the received data stream to a standardized format, and then divides it into data frames of a fixed size, thereby ensuring that each frame of data can be independently feature extracted. The feature extraction operation refers to extracting specific content features from the network decoded data after framing, such as data length, keywords, special characters, sensitive words, and multimedia features. The core of this operation is to ensure that important features in the data are retained to provide support for subsequent feature analysis and classification. The feature extraction operation identifies preset key features, such as sensitive words and multimedia tags, from the data through natural language processing and pattern recognition algorithms, making the attributes of the data clearer. Exemplarily, in an embodiment of the present invention, the natural language processing algorithm used is a sensitive word recognition algorithm and a regular expression matching algorithm based on term frequency-inverse document frequency (TF-IDF). Of course, depending on the actual application situation, the natural language processing algorithm can also use a word vector model (such as Word2Vec), a sentiment analysis algorithm, etc.; the pattern recognition algorithm can use a convolutional neural network (CNN) or a support vector machine (SVM) for feature detection and classification, which is not limited by the present invention.

[0090] It should be noted that the feature vector generation operation refers to converting the extracted content features into a vector form for numerical calculation and analysis. The core is to convert multiple features of the data into a unified vector form to adapt to subsequent quantitative scoring and model training. The feature vector generation operation uses a feature encoding algorithm to map various features such as data length, keyword frequency, special character distribution, sensitive word ratio, etc. to a specific vector dimension, so that each piece of network information data can be represented by a feature vector. The generated feature vector provides an analyzable input for the classification model and supports efficient processing of data classification. Exemplarily, in an embodiment of the present invention, the feature encoding algorithm used is One-Hot Encoding, which is used to convert discrete features into numerical vectors. Of course, depending on the actual application situation, the feature encoding algorithm can also use word embedding (such as Word Embeddings) or multidimensional scaling (MDS) and other technologies, which are not limited by the present invention. The quantitative scoring operation refers to scoring each piece of network information data according to the generated feature vector to reflect its importance and sensitivity. The core of this operation is to convert the numerical representation of the feature into a quantitative score through a preset scoring rule, so as to more intuitively measure the classification attributes of the data. Exemplarily, in an embodiment of the present invention, the quantitative scoring operation calculates the final score according to the value of each feature vector dimension and the importance weight, thereby obtaining the scoring result of each data. The quantitative scoring is used to determine the importance and sensitivity of the data, providing a judgment basis for subsequent encryption and security processing, and ensuring that key data can be effectively protected.

[0091] In step S13, the single character value is calculated according to the network information data, and an encrypted character set is obtained according to the single character value, including:

[0092] The value of a single character is calculated using the following formula:

[0093]

[0094] Perform a character mapping operation according to the single character value to obtain an encrypted character set;

[0095] in, is the sensitivity coefficient; is the importance variable coefficient; is the random number variable coefficient; Variable coefficient for data type; The variable coefficient for the data format; is the index value of data sensitivity and importance; Index value for data type and data format; A single character value representing the encrypted output; It is the multiplier constant used for encryption, which is used to control the magnification or reduction effect during the encryption process.

[0096] It should be noted that, in the present invention, the encryption character set is used to encode and encrypt network information data for output. The structure of the encryption formula uses a nested multiplication and addition operation to achieve data encryption conversion. In the formula, It represents the sensitivity coefficient, which is used to measure the sensitivity of data in network information. For example, data involving personal privacy may be assigned a higher values ​​to increase the complexity of its encryption. These coefficients can be obtained through sensitivity analysis of the information content. The importance variable coefficient represents the importance weight of the data and is used to determine the priority of different data in the encryption process. The importance variable coefficient is usually determined by analyzing the content characteristics of network information data. It is a random number variable coefficient, which is a random variable introduced in the encryption process to ensure that the same data has different encryption results in different encryption operations. The value of can be dynamically generated by a random number generator to increase the unpredictability of the encryption. The data type variable coefficient is used to distinguish different types of data (such as text, image, audio, etc.) and assign different encryption weights to different data types. The coefficient is pre-set according to the data type to ensure that each data type is properly processed during the encryption process. The data format variable coefficient represents the format characteristics of the data (such as XML, JSON, etc.), which is used to adjust the encryption parameters so that different formats of the same data type can maintain specific differences when encrypted. The single character value representing the encrypted output is the encryption result of each character calculated by the formula. Its value is affected by various parameters and coefficients. It is a multiplier constant used for encryption. Its value can be adjusted according to the encryption requirements to enlarge or reduce the amplitude of the encrypted output character value, thereby changing the encrypted data distribution.

[0097] It should be noted that, in step S13, the purpose of calculating a single character value and performing a character mapping operation is to convert the network information data into an encrypted character set, thereby realizing the concealment and protection of data. The character mapping operation refers to further converting the calculated single character value to obtain the corresponding encrypted character. According to the single character value, it is converted into a character in the encrypted character set through a mapping algorithm or by looking up a mapping table. The character mapping operation is used to convert digitized data into recognizable encrypted characters, thereby forming a complete encrypted character set, which is convenient for data storage and transmission. Exemplarily, in an embodiment of the present invention, the character mapping operation can use ASCII code mapping, Base64 encoding, etc. to map a single character value to a corresponding character set. Of course, the specific mapping method can be selected according to actual needs, and the present invention is not limited to this.

[0098] In step S14, the encryption matrix of the network information data is constructed according to the network information data and the encryption character set to obtain the encryption matrix of the network information data, including:

[0099] Calculate the sensitivity and importance of the network information data according to the network information data and the encrypted character set, and obtain the sensitivity variable coefficient and the importance variable coefficient in the encrypted character set;

[0100] According to the network information data and the encryption character set, a data type analysis of the network information data is performed to obtain a data type variable coefficient and a data format variable coefficient in the encryption character set;

[0101] According to the network information data and the encryption character set, random number variable coefficients are randomly generated to obtain random number variable coefficients in the encryption character set;

[0102] An encryption matrix is ​​generated according to the network information data, the encryption character set, the sensitivity variable coefficient, the importance variable coefficient, the data type variable coefficient, the data format variable coefficient and the random number variable coefficient to obtain the encryption matrix of the network information data.

[0103] It should be noted that in the present invention, the encryption matrix construction operation is used to generate an encryption matrix suitable for diversified network information data, so that different data can be encrypted according to their sensitivity, importance, data type and format characteristics. According to the content of the network information data, its sensitivity and importance are calculated. For example, the content involving privacy information may be assigned a higher sensitivity coefficient, while the core data may be assigned a higher importance coefficient. These coefficients determine the priority of each data element in the encryption process, so that more sensitive or important data has higher security protection when encrypted. The data type variable coefficient and the data format variable coefficient determine the corresponding coefficient by analyzing the type (such as text, image, audio) and data format (such as JSON, XML) of the network information data. These coefficients distinguish data of different types and formats in the encryption matrix, so that the encryption strategy can adapt to diversified data forms, thereby improving the applicability of encryption. In the encryption process, a dynamic random variable is generated by a random number generator. The random number coefficient increases the unpredictability of encryption, so that even the same data content will obtain different encryption results in each encryption process, further enhancing data security. The final encryption matrix is ​​used for actual encryption operations, and the network information data is represented in matrix form, making the encryption process more organized and systematic. The generation of the encryption matrix ensures that network information data is fully and effectively protected during the encryption process, and can perform flexible encryption processing based on data characteristics.

[0104] The step of generating an encryption matrix based on the network information data, the encryption character set, the sensitivity variable coefficient, the importance variable coefficient, the data type variable coefficient, the data format variable coefficient and the random number variable coefficient to obtain the encryption matrix of the network information data includes:

[0105] Generate an m×n data matrix according to the network information data and the encryption character set to obtain an initial encryption matrix;

[0106] According to the initial encryption matrix, the sensitivity variable coefficient and the importance variable coefficient are assigned a value to obtain a sensitivity importance matrix;

[0107] According to the sensitivity importance matrix, the data type variable coefficient and the data format variable coefficient are assigned a value to obtain a data feature matrix;

[0108] According to the data feature matrix, the random number variable coefficients are assigned values ​​to obtain an encryption transformation matrix;

[0109] According to the encryption transformation matrix, the parameters in the encryption character set are matrixed to obtain the final encryption matrix of the network information data.

[0110] It is worth noting that in the encryption matrix generation process of the present invention, the assignment and operation steps of various parameters are intended to establish a multi-dimensional encryption framework to ensure the security and specificity of network information data. The initial encryption matrix is ​​an m×n data matrix, which is generated according to the network information data and the encryption character set. The initial encryption matrix, as the basic framework of the encryption operation, contains the basic structure of the network information data and provides a data basis for the coefficient assignment and encryption operation in subsequent operations. The sensitivity importance matrix contains the assignment operation results of the sensitivity variable coefficient and the importance variable coefficient. According to the content characteristics and encryption requirements of the network information data, the sensitivity and importance coefficients are assigned and obtained. The matrix is ​​used to distinguish the sensitivity and importance of different data in the encryption process, so that the encryption strength of the data can be proportional to its sensitivity and importance, thereby improving the protection strength of key data. The data feature matrix is ​​the result of the assignment operation based on the data type variable coefficient and the data format variable coefficient. By analyzing the specific data type (such as text, picture, audio, etc.) and format (such as JSON, XML, etc.), the corresponding type and format coefficient are assigned to each data item. The data feature matrix reflects the diversity and multi-dimensional characteristics of network information data, so that the encryption method can adapt to data of different types and formats, and improve the flexibility and adaptability of encryption. The encryption transformation matrix contains the result of the assignment operation of the random number variable coefficient (L). During the encryption process, dynamic random number variable coefficients are injected into the data matrix to increase the randomness of the encryption operation. The introduction of random numbers increases the unpredictability of encryption. Even the same data will generate different encryption results in different encryption processes, thereby further enhancing the confidentiality and security of the data. The final encryption matrix is ​​the collective result of all the aforementioned assignments and operations. All parameters in the encryption character set are matrixed, and the final encryption matrix is ​​constructed by combining the sensitivity importance matrix, the data feature matrix and the encryption transformation matrix. The final encryption matrix is ​​used for actual encryption operations to convert network information data into encrypted information to ensure the confidentiality and integrity of data during transmission and storage. Exemplarily, in an embodiment of the present invention, the random number variable coefficient can be generated by a pseudo-random number generator, or a real hardware random number generator can be used, which can be flexibly selected according to the application scenario requirements. The present invention is not limited to this. The generation of the final encryption matrix allows the data to fully consider the multi-dimensional factors of sensitivity, importance, data type, data format and randomness during the encryption process, thereby achieving efficient and reliable data protection.

[0111] In step S15, the network information data is classified according to the preset network information data importance sensitivity to obtain network information classification data, including:

[0112] Perform sensitivity analysis based on the network information data to obtain sensitivity data;

[0113] Performing importance analysis based on the network information data to obtain importance data;

[0114] According to the sensitivity data and the importance data, encryption strategies for different types of data are determined to obtain network information classification data.

[0115] The calculation formulas for the sensitivity analysis and the importance analysis are as follows:

[0116] The calculation formula for sensitivity analysis is:

[0117]

[0118] in, is the sensitive information ratio factor; Sensitive information data; It is non-sensitive information data; is the initial value; The data is sensitive;

[0119] The calculation formula for importance analysis is:

[0120]

[0121] in, is the adjustment factor; is the initial important information length; The number of data partitions for network information; is the initial value; Importance data.

[0122] It should be noted that, in the embodiment of the present invention, the generation process of network information classification data is intended to classify network data based on sensitivity and importance, so as to select a suitable encryption strategy in the subsequent encryption process to ensure the security and confidentiality of the data. Sensitivity analysis is a quantitative assessment of the content sensitivity of network information data. By analyzing the content characteristics of network information data, such as the keywords, sensitive words or specific data types (such as identity information, financial data, etc.) contained, its sensitivity is obtained. The results of sensitivity analysis are used to evaluate the privacy and confidentiality requirements of network information data and provide a basis for the subsequent encryption strategy selection. Sensitive data usually requires stronger encryption algorithms and higher protection strength. Importance analysis is a process of evaluating the criticality and priority of network information data. According to the actual use and business logic of network information data, its importance in the overall system is analyzed. Important data is usually crucial to business operations and has a high value. The results of importance analysis are used to judge the core position and protection requirements of data in the system. Data with higher importance will be assigned to encryption strategies with higher priority to ensure that it has higher security under information leakage or attack. Encryption strategy determination is based on sensitivity data and importance data to select suitable encryption algorithms and security protection schemes for different types of data. By comprehensively analyzing the results of sensitivity analysis and importance analysis, appropriate encryption strength, encryption algorithm (such as symmetric encryption or asymmetric encryption), and additional protection measures (such as data tagging or watermarking) are selected. The results determined by the encryption policy generate network information classification data so that each type of data can be matched with encryption protection. This process ensures the efficient use of system resources while ensuring that the security requirements of different data are reasonably met. Exemplarily, in an embodiment of the present invention, sensitivity analysis can use a natural language processing algorithm based on machine learning to automatically analyze the data content, and importance analysis can be evaluated with reference to a preset business rule table or system authority level. Of course, the specific sensitivity and importance analysis methods can be adjusted according to actual application requirements, and the present invention does not limit this. Ultimately, through reasonable encryption policy allocation, classified encryption protection of different network information data can be achieved, ensuring data security while improving the efficiency of system encryption processing.

[0123] In step S16, the data relationship analysis is performed based on the encryption matrix and the network information classification data to obtain an encryption importance matrix, including:

[0124] Perform data comparison and analysis based on the encryption matrix and the network information classification data to obtain matrix difference data;

[0125] Perform information encryption matching according to the matrix difference data to obtain an encrypted matching result;

[0126] According to the encrypted matching result, construct a data matrix having a matrix difference length to obtain a second data matrix;

[0127] According to the second data matrix, an inverse matrix is ​​generated by matrix operation to obtain data corresponding to the matrix;

[0128] A matrix construction operation is performed according to the matrix corresponding data to obtain an encrypted importance matrix.

[0129] It should be noted that, in the embodiment of the present invention, the generation process of the encryption importance matrix is ​​intended to determine the importance of data through a comprehensive analysis of the encryption matrix and the network information classification data, so as to optimize the encryption strategy and resource allocation. Data comparison analysis is a process of calculating the difference between the encryption matrix and the network information classification data. According to the parameters in the encryption matrix and the classification data, a comparison is performed item by item, and the difference between the two is calculated to obtain matrix difference data. Data comparison analysis is used to evaluate the degree of matching between the encryption matrix and the classification data in terms of importance. The difference data can reveal potential inconsistencies in the data and help optimize subsequent encryption processing. Information encryption matching is to compare the encryption parameters in the encryption matrix and the classification data to check their matching degree in terms of data classification. According to the matrix difference data, the compliance of different data items with the encryption requirements is further analyzed to obtain the encryption matching result. The encryption matching result is used to judge the adaptability of the data to the classification standard and the rationality of the encryption strategy, and provide a guiding basis for the subsequent matrix generation. The second data matrix is ​​a new matrix generated based on the matrix difference data, and its length corresponds to the length of the difference data. By constructing a new data matrix according to a preset logic based on the matrix difference data. The second data matrix is ​​the basis for subsequent inverse matrix operations, ensuring the accuracy and completeness of data analysis.

[0130] Among them, it is worth noting that the inverse matrix generation is an operation obtained by performing matrix operations on the second data matrix, and the generated inverse matrix represents the matrix corresponding data. The second data matrix is ​​inversely operated to generate matrix corresponding data reflecting encryption requirements and data classification characteristics. The inverse matrix generation ensures the reversibility and consistency of the data during the encryption process, and lays the foundation for the final construction of the encryption importance matrix. The encryption importance matrix is ​​a comprehensive reflection of data classification, encryption requirements and encryption matching results, and is used to represent the encryption priority of the data. According to the matrix corresponding data, an encryption importance matrix containing various encryption priorities and importance is constructed. The encryption importance matrix is ​​used to determine the importance level of various types of data in the encryption process, help allocate system resources, optimize encryption strength and priority. Exemplarily, in an embodiment of the present invention, data comparison and analysis adopts a differential operation algorithm, information encryption matching is realized by a conditional matching algorithm, and the inverse matrix generation adopts an inverse operation method based on linear algebra. Of course, the specific implementation method can be selected according to the actual application requirements, and the present invention is not limited to this.

[0131] In step S17, data encryption is performed and transmitted according to the network information data and the encryption importance matrix to achieve secure transmission of the network information data.

[0132] It should be noted that, in the embodiment of the present invention, the purpose of the data encryption and transmission process is to use the encryption importance matrix to perform hierarchical encryption processing on the network information data to achieve safe and efficient transmission. Data encryption is to perform encryption operations of different strengths on the network information data according to the importance level in its encryption importance matrix. According to the encryption importance matrix generated above, various types of data items in the network information data are encrypted separately; high-importance data use a stronger encryption algorithm, and low-importance data use a relatively simple encryption method. Data transmission is the process of securely sending encrypted network information data on the network. After completing the data encryption, the encrypted data is transmitted to the receiving end through a secure transmission protocol (such as HTTPS or other encrypted communication protocols). Exemplarily, in the embodiment of the present invention, the data encryption operation uses the AES encryption algorithm, and the transmission process uses a security protocol based on SSL / TLS. Of course, the specific encryption algorithm and transmission protocol can be selected according to the actual application requirements, and the present invention does not limit this.

[0133] Reference Figure 2 The second embodiment of the present invention provides a network information content encryption system, comprising:

[0134] A data acquisition module is used to acquire network data in network traffic in real time;

[0135] A data preprocessing module, used to perform data preprocessing according to the network data to obtain preprocessed network information data;

[0136] An encryption character module, used for calculating a single character value according to the network information data, and obtaining an encryption character set according to the single character value;

[0137] An encryption matrix module, used to construct an encryption matrix of the network information data according to the network information data and the encryption character set, to obtain an encryption matrix of the network information data;

[0138] An information classification module, used to classify the network information data according to the preset network information data importance sensitivity to obtain network information classification data;

[0139] An importance module, used to perform data relationship analysis based on the encryption matrix and the network information classification data to obtain an encryption importance matrix;

[0140] The encryption module is used to encrypt and transmit the data according to the network information data and the encryption importance matrix to achieve secure transmission of the network information data.

[0141] It should be noted that the network information content encryption system provided in the embodiment of the present invention is used to execute all the process steps of the network information content encryption method in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so they will not be repeated.

[0142] In summary, in the present invention, the network data in the network traffic is obtained in real time, and the network data is preprocessed to obtain the preprocessed network information data, and then an encryption character set is constructed to construct an encryption matrix for the network information data, and then the data is classified according to the preset network information data importance sensitivity to obtain network information classification data, and then the data relationship analysis is performed to obtain the encryption importance matrix, and finally the data is encrypted and transmitted according to the encryption importance matrix. Among them, the encryption character set realizes the quantitative characterization of the differences in network information data by introducing multiple parameters such as sensitivity variable coefficient, importance variable coefficient, data type variable coefficient, etc., and can perform differential encryption according to the importance and sensitivity of the data. In the encryption process, the encryption matrix and the encryption importance matrix are used simultaneously to encrypt the data, which not only ensures the security of important sensitive data, but also avoids excessive encryption of ordinary data.

[0143] The embodiment of the present invention further provides a terminal device. The terminal device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a network information content encryption program. When the processor executes the computer program, the steps in the above-mentioned embodiments of the network information content encryption method are implemented, such as Figure 1 Alternatively, the processor implements the functions of each module / unit in the above-mentioned system embodiments when executing the computer program.

[0144] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the terminal device.

[0145] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of terminal devices and do not constitute a limitation on the terminal device. The terminal device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the terminal device may also include input and output devices, network access devices, buses, etc.

[0146] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0147] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the terminal device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0148] Wherein, if the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or system capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0149] It should be noted that the system embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the system embodiment provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0150] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for encrypting network information content, characterized in that: The following steps are involved: Get network data from network traffic in real time; Performing data preprocessing according to the network data to obtain preprocessed network information data; Calculating a single character value according to the network information data, and obtaining an encrypted character set according to the single character value; According to the network information data and the encryption character set, an encryption matrix of the network information data is constructed to obtain an encryption matrix of the network information data; According to the network information data, data classification is performed according to preset network information data importance sensitivity to obtain network information classification data; Performing data relationship analysis based on the encryption matrix and the network information classification data to obtain an encryption importance matrix; According to the network information data and the encryption importance matrix, data encryption and transmission are performed to achieve secure transmission of the network information data; The step of calculating a single character value according to the network information data and obtaining an encrypted character set according to the single character value comprises: The value of a single character is calculated using the following formula: According to the single character value, convert it into a character in the encrypted character set by a mapping algorithm or by looking up a mapping table, so as to obtain a complete encrypted character set; in, is the sensitivity coefficient; is the importance variable coefficient; is the random number variable coefficient; Variable coefficient for data type; The variable coefficient for the data format; is the index value of data sensitivity and importance; Index value for data type and data format; A single character value representing the encrypted output; It is the multiplier constant used for encryption, which is used to control the magnification or reduction effect during the encryption process.

2. The method for encrypting network information content according to claim 1, characterized in that: The method of performing data preprocessing according to the network data to obtain preprocessed network information data includes: According to the network information data, decoding and framing preprocessing are performed to obtain network decoded data; Extracting features based on the network decoding data to obtain content features; Generate a feature vector according to the content feature to obtain a network feature vector; According to the feature vector, quantitative scoring is performed to obtain pre-processed network information data; The content features include data length, keywords, special characters, sensitive words and multimedia features.

3. The method for encrypting network information content according to claim 1, characterized in that: The step of constructing an encryption matrix of the network information data according to the network information data and the encryption character set to obtain the encryption matrix of the network information data includes: Calculate the sensitivity and importance of the network information data according to the network information data and the encrypted character set, and obtain the sensitivity variable coefficient and the importance variable coefficient in the encrypted character set; According to the network information data and the encryption character set, a data type analysis of the network information data is performed to obtain a data type variable coefficient and a data format variable coefficient in the encryption character set; According to the network information data and the encryption character set, random number variable coefficients are randomly generated to obtain random number variable coefficients in the encryption character set; An encryption matrix is ​​generated according to the network information data, the encryption character set, the sensitivity variable coefficient, the importance variable coefficient, the data type variable coefficient, the data format variable coefficient and the random number variable coefficient to obtain the encryption matrix of the network information data.

4. The method for encrypting network information content according to claim 3, characterized in that: The method of generating an encryption matrix according to the network information data, the encryption character set, the sensitivity variable coefficient, the importance variable coefficient, the data type variable coefficient, the data format variable coefficient and the random number variable coefficient to obtain the encryption matrix of the network information data includes: Generate an m×n data matrix according to the network information data and the encryption character set to obtain an initial encryption matrix; According to the initial encryption matrix, the sensitivity variable coefficient and the importance variable coefficient are assigned a value to obtain a sensitivity importance matrix; According to the sensitivity importance matrix, the data type variable coefficient and the data format variable coefficient are assigned a value to obtain a data feature matrix; According to the data feature matrix, the random number variable coefficients are assigned values ​​to obtain an encryption transformation matrix; According to the encryption transformation matrix, the parameters in the encryption character set are matrixed to obtain the final encryption matrix of the network information data.

5. The method for encrypting network information content according to claim 1, characterized in that: The method of classifying the network information data according to the preset network information data importance sensitivity to obtain network information classification data includes: Perform sensitivity analysis based on the network information data to obtain sensitivity data; Performing importance analysis based on the network information data to obtain importance data; According to the sensitivity data and the importance data, encryption strategies for different types of data are determined to obtain network information classification data.

6. The method for encrypting network information content according to claim 5, characterized in that: The calculation formulas for the sensitivity analysis and the importance analysis are as follows: The calculation formula for sensitivity analysis is: in, is the sensitive information ratio factor; Sensitive information data; It is non-sensitive information data; is the initial value; The data is sensitive; The calculation formula for importance analysis is: in, is the adjustment factor; is the initial important information length; The number of data partitions for network information; is the initial value; Importance data.

7. The method for encrypting network information content according to claim 1, characterized in that: The step of performing data relationship analysis based on the encryption matrix and the network information classification data to obtain an encryption importance matrix includes: Perform data comparison and analysis based on the encryption matrix and the network information classification data to obtain matrix difference data; Perform information encryption matching according to the matrix difference data to obtain an encrypted matching result; According to the encrypted matching result, construct a data matrix having a matrix difference length to obtain a second data matrix; According to the second data matrix, an inverse matrix is ​​generated by matrix operation to obtain data corresponding to the matrix; A matrix construction operation is performed according to the matrix corresponding data to obtain an encrypted importance matrix.

8. A network information content encryption system, used to implement the network information content encryption method according to any one of claims 1 to 7, characterized in that: include: A data acquisition module is used to acquire network data in network traffic in real time; A data preprocessing module, used to perform data preprocessing according to the network data to obtain preprocessed network information data; An encryption character module, used for calculating a single character value according to the network information data, and obtaining an encryption character set according to the single character value; An encryption matrix module, used to construct an encryption matrix of the network information data according to the network information data and the encryption character set, to obtain an encryption matrix of the network information data; An information classification module, used to classify the network information data according to the preset network information data importance sensitivity to obtain network information classification data; An importance module, used to perform data relationship analysis based on the encryption matrix and the network information classification data to obtain an encryption importance matrix; The encryption module is used to encrypt and transmit the data according to the network information data and the encryption importance matrix to achieve secure transmission of the network information data.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the network information content encryption method according to any one of claims 1 to 7.

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