Intelligent campus OA office data interaction method, device and equipment and medium

Abstract

The invention is suitable for the technical field of data encryption, and provides an intelligent campus OA office data interaction method, device, equipment and medium, the intelligent campus OA office data interaction method comprises the following steps: a cloud server receives a data extraction request sent by an OA client, and extracts original data corresponding to the data extraction request; the cloud server segments the original data according to a fixed size to obtain a plurality of original data blocks; the cloud server encrypts the odd original data block set and the even original data block set through the key set to obtain a first ciphertext corresponding to the odd original data block set and a second ciphertext corresponding to the even original data block set; and the cloud server sequentially sends the first ciphertext and the second ciphertext to the OA client. According to the technical scheme, through a data block encryption mechanism, the security of data interaction in the OA system is improved, and the flexibility of data processing and the system performance are greatly improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data encryption, and in particular relates to a smart campus OA office data interaction method, device, equipment and medium. Background Art

[0002] With the rapid development of the information age, digital office has become an important part of modern campus management. Office Automation (OA system) in campus management is increasingly used in administrative management, teaching arrangements, student affairs, financial management and other fields, greatly improving the efficiency and information processing capabilities of various office activities on campus. OA system is usually composed of cloud servers and various clients (such as PC, mobile, etc.). Through real-time data interaction between cloud servers and clients, data storage, processing, sharing and application are more efficient.

[0003] However, with the widespread application of OA systems in campuses, data security and privacy protection have become urgent issues to be addressed. OA systems involve a large amount of sensitive data, such as classified archives, academic materials, financial information, or faculty information. Once these data are leaked or maliciously tampered with, they may have a serious impact on the school's management work and may even threaten the personal privacy of students, teachers, and other relevant personnel. Therefore, how to ensure the security of data in OA systems, especially during data transmission and storage, has become an important issue in the design and implementation of current campus OA systems.

[0004] At present, certain encryption technologies have been widely used in OA systems for data security. For example, by encrypting sensitive data, data can be effectively prevented from being intercepted or tampered with during transmission. However, the data encryption methods in the prior art often have some shortcomings. For example, data encryption usually encrypts the entire data and lacks flexibility for different types of data. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a smart campus OA office data interaction method, device, equipment and medium to solve the technical problem that data encryption usually encrypts the entire data and lacks flexibility for different types of data.

[0006] A first aspect of an embodiment of the present invention provides an intelligent campus OA office data interaction method, the intelligent campus OA office data interaction method is applied to an OA system, the OA system includes a cloud server and an OA client, the intelligent campus OA office data interaction method includes: The cloud server receives the data extraction request sent by the OA client, and extracts the original data corresponding to the data extraction request; The cloud server matches a preset key set corresponding to the sensitivity level according to the sensitivity level of the original data; The cloud server divides the original data into fixed sizes to obtain multiple original data blocks; The cloud server extracts the odd-numbered original data block set and the even-numbered original data block set respectively according to the order of the multiple original data blocks in the original data; The cloud server encrypts the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set; The cloud server sends the first ciphertext and the second ciphertext to the OA client in sequence.

[0007] Furthermore, before the step of matching the preset key set corresponding to the sensitivity level according to the sensitivity level of the original data, the cloud server further includes: Randomly generate initial keys corresponding to different sensitivity levels, and send the initial keys to the OA client; the OA client is used to generate a key set according to the initial keys; Splitting the initial key to obtain multiple first subkeys; Performing cyclic shift processing on the multiple first subkeys to obtain multiple second subkeys; The key set is obtained by performing convolution calculation based on the multiple first subkeys and the multiple second subkeys.

[0008] Furthermore, the step of performing convolution calculation based on the multiple first subkeys and the multiple second subkeys to obtain the key set includes: Based on the multiple first subkeys, construct a first convolution kernel; Arranging the plurality of first subkeys according to preset positions to form a first data matrix; Performing convolution processing on the plurality of the first data matrices respectively by using the first convolution kernel to obtain a plurality of first target keys; Based on the multiple second subkeys, construct a second convolution kernel; Arranging the plurality of second sub-keys according to preset positions to construct a second data matrix; Performing convolution processing on the plurality of second data matrices respectively by using the second convolution kernel to obtain a plurality of second target keys; A plurality of first target keys and a plurality of second target keys are used as the key set.

[0009] Furthermore, the step of constructing a first convolution kernel based on the multiple first subkeys includes: Extracting the first two characters and the last two characters of the plurality of first subkeys respectively; Constructing the first two characters and the last two characters corresponding to each of the first subkeys into a first convolution kernel according to a preset element position; Correspondingly, the step of constructing a second convolution kernel based on the multiple second subkeys includes: extracting first two characters and last two characters of a plurality of said second subkeys respectively; The first two characters and the last two characters corresponding to each of the plurality of the second subkeys are constructed into a second convolution kernel according to preset element positions.

[0010] Furthermore, the cloud server encrypts the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set, including: Based on a plurality of first target keys in the key set, encrypting the odd-numbered original data block set in order to obtain a first ciphertext corresponding to the odd-numbered original data block set; Based on the multiple second target keys in the key set, the even-numbered original data block set is encrypted in sequence to obtain a second ciphertext corresponding to the even-numbered original data block set.

[0011] Furthermore, the step of the cloud server sending the first ciphertext and the second ciphertext to the OA client in sequence includes: The first ciphertext, the sequence number corresponding to the sensitivity level, the original data sequence number, the sequence number corresponding to the first ciphertext, and the number of ciphertexts are respectively encapsulated into a data packet to obtain a plurality of first data packets corresponding to the first ciphertext; the sequence number corresponding to the first ciphertext is used to instruct the OA client to combine the original data blocks corresponding to the first ciphertext in sequence to obtain the original data; The second ciphertext, the sequence number corresponding to the sensitivity level, the original data sequence number, the sequence number corresponding to the second ciphertext, and the number of ciphertexts are respectively encapsulated into a data packet to obtain a plurality of second data packets corresponding to the second ciphertext; the sequence number corresponding to the second ciphertext is used to instruct the OA client to combine the original data blocks corresponding to the second ciphertext in sequence to obtain the original data; Send multiple first data packets and multiple second data packets to the OA client in sequence.

[0012] Further, after the step of sequentially sending the plurality of first data packets and the plurality of second data packets to the OA client, the method further includes: The OA client receives a plurality of first data packets and a plurality of second data packets sent by the cloud server; If the number of the plurality of first data packets and the plurality of second data packets is consistent with the number of ciphertexts, the OA client matches the corresponding sensitivity level according to the sequence number corresponding to the sensitivity level; The OA client matches the initial key corresponding to the sensitivity level and generates a key set according to the initial key; The OA client decrypts the first ciphertext and the second ciphertext according to the key set, the sequence number corresponding to the first ciphertext, and the sequence number corresponding to the second ciphertext to obtain a plurality of original data blocks; The OA client combines the multiple original data blocks according to the sequence numbers corresponding to the first ciphertexts and the sequence numbers corresponding to the second ciphertexts to obtain the original data.

[0013] A second aspect of an embodiment of the present invention provides an intelligent campus OA office data interaction device, including: A first extraction unit, configured to receive, by the cloud server, a data extraction request sent by the OA client, and extract original data corresponding to the data extraction request; A matching unit, configured for the cloud server to match a preset key set corresponding to the sensitivity level according to the sensitivity level of the original data; A segmentation unit, used for the cloud server to segment the original data according to a fixed size to obtain a plurality of original data blocks; A second extraction unit is used for the cloud server to extract the odd-numbered original data block set and the even-numbered original data block set respectively according to the order of the multiple original data blocks in the original data; An encryption unit is used for the cloud server to encrypt the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set; The sending unit is used for the cloud server to send the first ciphertext and the second ciphertext to the OA client in sequence.

[0014] The third aspect of an embodiment of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the smart campus OA office data interaction method described in the first aspect are implemented.

[0015] The fourth aspect of an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the smart campus OA office data interaction method described in the first aspect are implemented.

[0016] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: according to the sensitivity level of the data, an appropriate encryption key is dynamically selected for encryption processing, avoiding the one-size-fits-all approach in the traditional encryption method. Different encryption strategies are used to process data of different sensitivity levels, ensuring that important data is protected with higher intensity. This solution makes the data encryption process more flexible and sophisticated by dividing the original data into fixed sizes and encrypting them in groups according to the parity of the data blocks. Different data blocks are encrypted with different keys, which enhances the system's processing ability for different types of data. In addition, the block processing of data enables the cloud server to process different data blocks in parallel or asynchronously, thereby improving encryption efficiency and reducing processing delay. Especially in the case of a large amount of data, this method can better optimize the encryption process, reduce the burden on the server, and improve the data interaction speed and response performance of the OA system. This solution not only ensures the security of the data, but also improves the efficiency of data interaction under the premise of ensuring security by segmenting, encrypting in parallel and encrypting on demand the data blocks. The cloud server can quickly send the encrypted data to the OA client, ensuring the confidentiality of the data during transmission, avoiding the leakage of sensitive data, and improving the fluency of data exchange. This technical solution not only improves the security of data interaction in the OA system through the data block encryption mechanism, but also greatly improves the flexibility of data processing and system performance. It has important application value for building a safe, efficient and easy-to-manage smart campus OA office system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A schematic flow chart of an intelligent campus OA office data interaction method provided by the present invention is shown; Figure 2 A schematic diagram of an intelligent campus OA office data interaction device provided by an embodiment of the present invention is shown; Figure 3 A schematic diagram of a terminal device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0019] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0020] The embodiments of the present invention provide a smart campus OA office data interaction method, device, equipment and medium to solve the technical problem that data encryption usually encrypts the entire data and lacks flexibility for different types of data.

[0021] First, the present invention provides a smart campus OA office data interaction method. Figure 1 , Figure 1 FIG. 1 is a schematic flow chart of a smart campus OA office data interaction method provided by the present invention. Figure 1 As shown, the smart campus OA office data interaction method may include the following steps: Step 101: The cloud server receives a data extraction request sent by the OA client, and extracts original data corresponding to the data extraction request; The OA client initiates a request to the cloud server. The data extraction request includes the identification or other filtering information about the required data. The cloud server extracts the corresponding original data from the database based on the received request.

[0022] Step 102: The cloud server matches a preset key set corresponding to the sensitivity level according to the sensitivity level of the original data; After extracting the original data, the cloud server extracts the sensitivity level of the data. Data of different sensitivity levels need to be encrypted using different keys. Sensitivity levels include but are not limited to low sensitivity level, medium sensitivity level and high sensitivity level. According to the sensitivity level, the cloud server selects a preset key set. The key set contains multiple subkeys to ensure the security and diversity of the encryption process. The calculation process of the key set is as follows: Optionally, before step 102, steps A1 to A4 are also included: Step A1: randomly generating initial keys corresponding to different sensitivity levels, and sending the initial keys to the OA client; the OA client is used to generate a key set according to the initial keys; Generate corresponding initial keys for different sensitivity levels (such as high sensitivity, medium sensitivity, low sensitivity, etc.). This is to ensure that the system can use different keys for encryption according to different security requirements. The key can be generated by a pseudo-random number generator to ensure that the generated key has different characteristics for each sensitivity level to enhance the security of the system.

[0023] Among them, the logic of generating the key set by the OA client is consistent with that of the cloud server, which will not be repeated here.

[0024] Step A2: Splitting the initial key to obtain multiple first subkeys; The initial key is "split" into multiple small subkeys to improve the flexibility and security of key use. Each subkey will participate in different encryption operations in subsequent processing.

[0025] Step A3: performing cyclic shift processing on the multiple first subkeys to obtain multiple second subkeys; Performing a "circular shift" on the first subkey can increase the complexity of the key and make it more difficult to crack. Circular shift refers to moving the bits in the key in a circular manner, which can be achieved through bitwise shift operations. The result of the circular shift is the generation of multiple new "second subkeys", which help to strengthen the unpredictability of the subsequent encryption process.

[0026] For example, the first subkey is "100011101011". After a circular shift one bit to the right, the second subkey is "110001110101".

[0027] Step A4: Perform convolution calculation based on the multiple first subkeys and the multiple second subkeys to obtain the key set.

[0028] Using convolution calculation, multiple first subkeys and second subkeys are combined to generate a new key set. It can be understood as fusing two sequences in a specific mathematical way. By combining subkeys from different sources, a more complex key set can be generated than the initial key, increasing the security of the system.

[0029] Specifically, step A4 includes steps A41 to A47: Step A41: constructing a first convolution kernel based on the multiple first subkeys; Multiple first subkeys are used to construct a convolution kernel, which is used to process the data matrix in subsequent calculations. The convolution kernel is usually a small-sized matrix that slides over the data matrix to perform convolution operations to extract features from the data. The "convolution kernel" here is actually a mathematical object that contains partial information of multiple first subkeys. The convolution kernel can be regarded as a fixed pattern or template extracted from the first subkey, which is used to extract features or encrypt input data.

[0030] Specifically, step A41 specifically includes: extracting the first two characters and the last two characters of the multiple first subkeys respectively; constructing the first two characters and the last two characters corresponding to the multiple first subkeys into a first convolution kernel according to preset element positions.

[0031] Step A42: Arrange the plurality of first subkeys according to preset positions to form a first data matrix; Arrange the multiple first subkeys according to a rule (such as a preset order or position) to form a data matrix. If the number of bits between the first subkeys is inconsistent, the number of bits between the multiple first subkeys can be aligned by filling in the bits with a preset value.

[0032] Step A43: performing convolution processing on the plurality of the first data matrices respectively by using the first convolution kernel to obtain a plurality of first target keys; Convolution is performed by sliding a convolution kernel over the data matrix. At each position, the convolution kernel is multiplied by a portion of the data matrix, and the results are summed to generate a new key element. The result of each convolution is a "first target key".

[0033] Step A44: constructing a second convolution kernel based on the multiple second subkeys; Specifically, step A44 specifically includes: extracting the first two characters and the last two characters of the plurality of second subkeys respectively; constructing the first two characters and the last two characters corresponding to the plurality of second subkeys into a second convolution kernel according to preset element positions.

[0034] Step A45: Arranging the plurality of second subkeys according to preset positions to construct a second data matrix; Step A46: performing convolution processing on the plurality of second data matrices respectively by using the second convolution kernel to obtain a plurality of second target keys; The logic of steps A44 to A46 is similar to that of steps A41 to A43, and will not be repeated here.

[0035] Step A47: Use multiple first target keys and multiple second target keys as the key set.

[0036] By constructing multiple first subkeys and second subkeys into a data matrix and performing convolution calculation using a convolution kernel, a target key with high complexity and unpredictability can be generated. This process makes the generation of the key not only rely on the simple operation of the initial key, but also increases the diversity of the key space through complex mathematical transformations, thereby greatly enhancing the difficulty of key cracking and the security of the system. By using the convolution kernel to perform convolution processing on the first data matrix and the second data matrix respectively, not only the randomness of the key distribution is improved, but also the security risks caused by the simple key relationship can be effectively avoided. Convolution calculation can capture and retain the complex associations between subkeys, ensuring that the generation of each target key has sufficient confidentiality and anti-attack. The technical solution ensures the structuring and standardization of the key generation process by constructing a convolution kernel and listing the subkeys as a data matrix according to a preset position. By performing convolution processing on the first subkey and the second subkey respectively, the generated multiple first target keys and multiple second target keys are combined into a key set, which can ensure the diversity within the key set. Through flexible convolution kernel design and matrix construction method, this solution can be adjusted according to different key lengths and structural requirements in practical applications. Through the preset position listing and structured data matrix construction method, the convolution calculation of the key can be carried out efficiently. In summary, the technical solution of the present invention generates a complex, diverse and highly secure key set through the convolution calculation method combined with multiple transformations of multiple first subkeys and second subkeys, which has significant security, efficiency and flexibility.

[0037] In this embodiment, by randomly generating initial keys corresponding to different sensitivity levels and sending these initial keys to the OA client for further processing, the risk of using static keys is avoided, the randomness and unpredictability of the keys are improved, and the security of the overall system is improved. After the initial key is processed by segmentation and cyclic shift, multiple subkeys are generated. By convolution calculation of multiple first subkeys and second subkeys, a key set with a complex structure is formed. This multi-level processing method not only increases the complexity of the key, but also makes the key set difficult to be reversed, thereby enhancing the anti-cracking ability of the system. Through multiple processing links such as segmentation, shifting and convolution calculation, the probability of key collision is effectively reduced, and possible key leakage problems are prevented. Even if an attacker obtains part of the key information, it is difficult to restore the complete key set through mathematical analysis, which greatly improves the confidentiality of the key. In summary, the technical solution enhances the security, flexibility and anti-attack ability of key management through a multi-level, dynamically generated key set design.

[0038] As an optional embodiment of the present application, the key set may also be generated in the following manner: The initial key is split to obtain multiple first subkeys, and the multiple first subkeys are substituted into the following function to obtain multiple first target keys: ; in, represents the ASCII code of the jth character of the i-th first target key, represents the ASCII code of the jth character of the i-th first subkey, represents the ASCII code of the j-1th character of the i-1th first subkey, represents the ASCII code of the j+1th character of the i-th first subkey, represents the ASCII code of the j-1th character of the i-th first subkey, Indicates modulo to ensure that the result is within the ASCII code range. Represents a bitwise exclusive OR operation, Indicates rounding down.

[0039] Boundary processing in this function: For j=1, use loop processing, that is, Considered as , m is the number of characters in the subkey.

[0040] For j=m, use loop processing, that is, Considered as .

[0041] For i=1, i.e. the initial subkey, a virtual pre-subkey can be set, which can be set to all zeros or all specific values.

[0042] The plurality of first subkeys are subjected to cyclic shift processing to obtain a plurality of second subkeys. The plurality of second keys are substituted into the above function to obtain a plurality of second target keys.

[0043] In cryptography, the XOR operation is used to implement simple encryption and decryption because it is a symmetric operation, that is, performing XOR operations on the same number twice can restore the original value. In the above function, the purpose of the XOR operation is mainly to confuse and increase the complexity of the calculation, ensuring that the changes of each character are not easy to predict. Each term in the function mixes the ASCII code of the current subkey character with the character of the previous subkey through XOR, so that each new subkey character is affected by the previous subkey character.

[0044] This section is used to further introduce ambiguity and nonlinear changes. In cryptography, by averaging, weighting, rounding, and other operations on input data (such as the ASCII value of a character), unpredictability can be effectively increased, making the generated new subkey more complex and difficult to recover by simple speculation. By adding and averaging the ASCII codes of two characters, the calculation of the current character can be combined with the relationship between the two characters before and after, avoiding relying on information from only a single character. This operation also introduces randomness and changes, so that each newly generated subkey character does not completely depend on its previous character, but on the historical information of the entire character sequence.

[0045] The above function performs a complex transformation on the characters of the subkey by taking an average and combining it with XOR, so that the calculation process of the new key characters is not linear, that is, it is not easy to deduce the new key through the simple mathematical relationship of the current characters. This nonlinearity helps to increase the difficulty for attackers to guess the new subkey. The function combines multiple operations such as XOR operation, weighted average, and modulus, which increases the difficulty for attackers to analyze the key pattern through simple algorithms. Even if the attacker can obtain part of the key or observe the law of key change, all these complex operations will bring huge computational challenges to the attacker. In the calculation process, the influence of the previous and next characters is cyclical, that is, the current character depends on the previous and next characters of the previous character. This feedback iterative process makes any slight change to the initial subkey be significantly reflected in the new subkey, increasing the difficulty of predicting the new subkey.

[0046] Step 103: The cloud server divides the original data into fixed sizes to obtain multiple original data blocks; The cloud server divides the original data into certain sizes. Usually, the size of each data block is fixed, which can facilitate subsequent parallel processing or encryption operations. After the division, the original data is split into multiple data blocks, each of which is a fragment of the original data.

[0047] Step 104: the cloud server extracts an odd-numbered original data block set and an even-numbered original data block set respectively according to the order of the multiple original data blocks in the original data; The cloud server divides the data blocks into two sets according to their order in the original data: one set contains data blocks with odd indexes and the other set contains data blocks with even indexes. This odd-even classification is to increase the complexity of the encryption process or to ensure the diversity of the encryption algorithm.

[0048] Step 105: The cloud server encrypts the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set; The cloud server encrypts the odd-numbered data block set and the even-numbered data block set according to the previously matched key set. The two sets use different keys. After encryption, the odd-numbered data block set generates the first ciphertext, and the even-numbered data block set generates the second ciphertext. In this way, the encryption of the original data is more detailed, avoiding the potential risks caused by the same encryption method for all data blocks.

[0049] Specifically, step 105 specifically includes: based on multiple first target keys in the key set, encrypting the odd original data block set in sequence to obtain a first ciphertext corresponding to the odd original data block set; based on multiple second target keys in the key set, encrypting the even original data block set in sequence to obtain a second ciphertext corresponding to the even original data block set.

[0050] If the number of original data blocks is greater than the target key, the target key is used cyclically for encryption. The specific process of encrypting data using a key is a traditional technology and will not be described in detail here.

[0051] Step 106: The cloud server sends the first ciphertext and the second ciphertext to the OA client in sequence.

[0052] The cloud server sends the two generated ciphertexts (the first ciphertext and the second ciphertext) to the OA client in sequence. After receiving the ciphertexts, the OA client decrypts them.

[0053] Specifically, step 106 specifically includes steps 1061 to 1063: Step 1061: respectively encapsulate the first ciphertext, the sequence number corresponding to the sensitivity level, the original data sequence number, the sequence number corresponding to the first ciphertext, and the number of ciphertexts into a data packet to obtain a plurality of first data packets corresponding to the first ciphertext; the sequence number corresponding to the first ciphertext is used to instruct the OA client to combine the original data blocks corresponding to the first ciphertext in sequence to obtain the original data; The package contents include: ①The first ciphertext: The encrypted data is the core content that needs to be transmitted.

[0054] ② Serial number corresponding to the sensitivity level: indicates the sensitivity level corresponding to the ciphertext, and is used to instruct the OA client to perform encryption processing of the corresponding sensitivity level.

[0055] ③ Original data serial number: identifies the location or number of the original data to which the ciphertext belongs, and instructs the OA client to correctly splice the data blocks after decryption.

[0056] ④ The sequence number corresponding to the first ciphertext: indicates the position of this ciphertext in the data block, ensuring that the OA client can reassemble the original data in sequence.

[0057] ⑤ Number of ciphertexts: Indicates how many parts are included in a set of ciphertexts, helping the client confirm whether all data has been received.

[0058] Step 1062: respectively encapsulate the second ciphertext, the sequence number corresponding to the sensitivity level, the original data sequence number, the sequence number corresponding to the second ciphertext, and the number of ciphertexts into a data packet to obtain a plurality of second data packets corresponding to the second ciphertext; the sequence number corresponding to the second ciphertext is used to instruct the OA client to combine the original data blocks corresponding to the second ciphertext in sequence to obtain the original data; Step 1063: Send the multiple first data packets and the multiple second data packets to the OA client in sequence.

[0059] By encapsulating the first ciphertext, the second ciphertext and their related information (such as sensitivity level, sequence number, original data sequence number, etc.) into a data packet and then sending it, the integrity and confidentiality of the data during the transmission process are effectively guaranteed. Each data packet contains the necessary context information, so that the OA client can accurately restore the original data, while avoiding the risk of data loss, tampering or leakage during the transmission process. The encapsulation of the ciphertext not only protects the privacy of the data, but also ensures that each data block can be reassembled in the correct order when the client decrypts it by dividing the data into multiple packets for sequential transmission. By instructing the OA client to combine the original data blocks according to the sequence number corresponding to the ciphertext, it can effectively prevent man-in-the-middle attacks or other forms of tampering and ensure the security of sensitive data. This solution provides good flexibility and scalability by independently encapsulating different ciphertexts and their related information. In practical applications, the cloud server can send different numbers of ciphertext data packets as needed to support data transmission requirements of different scales and security levels. This technical solution adapts to the needs of various different scenarios, whether it is the transmission of large amounts of data or the separate processing of data of different sensitivity levels, it can be efficiently implemented.

[0060] Optionally, after step 106, steps 107 to 111 are included: Step 107: The OA client receives a plurality of first data packets and a plurality of second data packets sent by the cloud server; The OA client receives data consisting of a plurality of first data packets and a second data packet from the cloud server. Each data packet contains metadata such as encrypted ciphertext, sensitivity level, and sequence information of the ciphertext. The OA client needs to correctly decrypt and restore the original data based on these metadata.

[0061] Step 108: If the number of the plurality of first data packets and the plurality of second data packets is consistent with the number of ciphertexts, the OA client matches the corresponding sensitivity level according to the sequence number corresponding to the sensitivity level; The OA client checks whether the number of the received multiple first data packets and second data packets is consistent with the number of ciphertexts to ensure that no data is lost. If the number of data packets is consistent, the OA client matches the corresponding sensitivity level according to the sequence number corresponding to the sensitivity level. The function of the sensitivity level is usually to distinguish different levels of data protection.

[0062] Step 109: The OA client matches the initial key corresponding to the sensitivity level, and generates a key set according to the initial key; The logic of the OA client generating a key set based on the initial key is the same as the logic of the cloud server generating a key set, so it will not be repeated here.

[0063] Step 110: The OA client decrypts the first ciphertext and the second ciphertext according to the key set, the sequence number corresponding to the first ciphertext, and the sequence number corresponding to the second ciphertext to obtain a plurality of original data blocks; The OA client uses the generated key set and the sequence number corresponding to the first ciphertext and the sequence number corresponding to the second ciphertext to decrypt the received first ciphertext and the second ciphertext. The sequence number corresponding to the first ciphertext and the sequence number corresponding to the second ciphertext here help the OA client understand the position of the decrypted text in the overall data and ensure the correct order of the decrypted data blocks.

[0064] Step 111: The OA client combines multiple original data blocks according to the sequence numbers corresponding to the first ciphertexts and the sequence numbers corresponding to the second ciphertexts to obtain original data.

[0065] The multiple original data blocks obtained by decryption are sequentially combined on the OA client according to their corresponding first ciphertext sequence number and second ciphertext sequence number. Each original data block has a corresponding sequence number, and the OA client splices the data blocks together according to these sequence numbers to ensure the integrity of data recovery.

[0066] The OA client ensures the correctness and integrity of each data packet in the data decryption process according to the consistency between the number of multiple first data packets and multiple second data packets and the number of ciphertexts. Through this verification mechanism, the OA client can determine whether a complete data packet is received, avoiding decryption failure or data loss caused by missing or wrong data. The OA client automatically matches the corresponding sensitivity level according to the sequence number corresponding to the sensitivity level, matches the initial key according to the sensitivity level, and generates an adaptive key set. This design makes the generation of keys more flexible and dynamic, and can automatically adjust the complexity and security of keys according to different sensitivity levels, thereby improving the security of the system when processing multiple sensitive data. By accurately matching and combining the sequence numbers of multiple original data blocks, the OA client can effectively combine the decrypted data blocks into complete original data in the correct order. Even if delays or packet loss occur during network transmission, as long as the OA client receives multiple complete data packets, it can rely on these sequence number information to accurately restore the original data, thereby improving the reliability of the decryption process. By matching the ciphertext sequence number and the key set and strictly encapsulating the data packets, the OA client can ensure the integrity of each ciphertext block during the decryption process. If data is tampered with or lost during transmission, the OA client can identify potential security issues by checking the consistency between the sequence number and the ciphertext, thereby enhancing the system's ability to protect against data tampering. The technical solution of the present invention not only improves the security, accuracy and efficiency of data decryption, but also enhances the flexibility, reliability and anti-tampering ability of the system by implementing dynamic key generation based on sensitivity level and accurate ciphertext sequence number matching on the OA client.

[0067] In this embodiment, according to the sensitivity level of the data, an appropriate encryption key is dynamically selected for encryption processing, avoiding the one-size-fits-all approach in traditional encryption methods. Different encryption strategies are used for data of different sensitivity levels to ensure that important data is protected with higher intensity. This solution makes the data encryption process more flexible and sophisticated by dividing the original data into fixed sizes and encrypting them in groups according to the parity of the data blocks. Different data blocks are encrypted with different keys, which enhances the system's processing ability for different types of data. In addition, the block processing of data enables the cloud server to process different data blocks in parallel or asynchronously, thereby improving encryption efficiency and reducing processing delays. Especially in the case of large amounts of data, this method can better optimize the encryption process, reduce the burden on the server, and improve the data interaction speed and response performance of the OA system. This solution not only ensures the security of the data, but also improves the efficiency of data interaction while ensuring security by segmenting, encrypting in parallel, and encrypting on demand the data blocks. The cloud server can quickly send the encrypted data to the OA client, ensuring the confidentiality of the data during transmission, avoiding the leakage of sensitive data, and improving the fluency of data exchange. This technical solution not only improves the security of data interaction in the OA system through the data block encryption mechanism, but also greatly improves the flexibility of data processing and system performance. It has important application value for building a safe, efficient and easy-to-manage smart campus OA office system.

[0068] like Figure 2 The present invention provides an intelligent campus OA office data interaction device, see Figure 2 , Figure 2 A schematic diagram of an intelligent campus OA office data interaction device provided by the present invention is shown, Figure 2 The smart campus OA office data interaction device shown includes: The first extraction unit 21 is used for the cloud server to receive the data extraction request sent by the OA client and extract the original data corresponding to the data extraction request; A matching unit 22, configured for the cloud server to match a preset key set corresponding to the sensitivity level according to the sensitivity level of the original data; A segmentation unit 23 is used for the cloud server to segment the original data according to a fixed size to obtain a plurality of original data blocks; A second extraction unit 24 is used for the cloud server to extract the odd-numbered original data block set and the even-numbered original data block set respectively according to the order of the multiple original data blocks in the original data; An encryption unit 25 is used for the cloud server to encrypt the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set; The sending unit 26 is used for the cloud server to send the first ciphertext and the second ciphertext to the OA client in sequence.

[0069] The present invention provides a smart campus OA office data interaction device, which dynamically selects appropriate encryption keys for encryption processing according to the sensitivity level of data, avoiding the one-size-fits-all approach in traditional encryption methods. Data of different sensitivity levels are processed using different encryption strategies to ensure that important data is protected with higher intensity. This solution makes the data encryption process more flexible and sophisticated by dividing the original data into fixed sizes and encrypting them in groups according to the parity of the data blocks. Different data blocks are encrypted with different keys, which enhances the system's processing ability for different types of data. In addition, the block processing of data enables the cloud server to process different data blocks in parallel or asynchronously, thereby improving encryption efficiency and reducing processing delay. Especially in the case of a large amount of data, this method can better optimize the encryption process, reduce the burden on the server, and improve the data interaction speed and response performance of the OA system. This solution not only ensures the security of data, but also improves the efficiency of data interaction under the premise of ensuring security by segmenting, encrypting in parallel and encrypting on demand the data blocks. The cloud server can quickly send the encrypted data to the OA client, ensure the confidentiality of the data during transmission, avoid the leakage of sensitive data, and improve the fluency of data exchange. This technical solution not only improves the security of data interaction in the OA system through the data block encryption mechanism, but also greatly improves the flexibility of data processing and system performance. It has important application value for building a safe, efficient and easy-to-manage smart campus OA office system.

[0070] Figure 3 Schematic diagram of a terminal device provided by an embodiment of the present invention. Figure 3 As shown, a terminal device 3 of this embodiment includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30, such as an intelligent campus OA office data interaction program. When the processor 30 executes the computer program 32, the steps in each of the above-mentioned intelligent campus OA office data interaction method embodiments are implemented, such as Figure 1 Alternatively, when the processor 30 executes the computer program 32, the functions of each unit in the above-mentioned device embodiments are realized, for example, Figure 2 Function of the unit shown.

[0071] Exemplarily, the computer program 32 may be divided into one or more units, which are stored in the memory 31 and executed by the processor 30 to complete the present invention. The one or more units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 32 in the terminal device 3. For example, the computer program 32 may be divided into the following specific functions of each unit: A first extraction unit, configured to receive, by the cloud server, a data extraction request sent by the OA client, and extract original data corresponding to the data extraction request; A matching unit, configured for the cloud server to match a preset key set corresponding to the sensitivity level according to the sensitivity level of the original data; A segmentation unit, used for the cloud server to segment the original data according to a fixed size to obtain a plurality of original data blocks; A second extraction unit is used for the cloud server to extract the odd-numbered original data block set and the even-numbered original data block set respectively according to the order of the multiple original data blocks in the original data; An encryption unit is used for the cloud server to encrypt the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set; The sending unit is used for the cloud server to send the first ciphertext and the second ciphertext to the OA client in sequence.

[0072] The terminal device includes but is not limited to a processor 30 and a memory 31. Those skilled in the art will appreciate that Figure 3 It is only an example of a terminal device 3 and does not constitute a limitation on the terminal device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device may also include input and output devices, network access devices, buses, etc.

[0073] The processor 30 may be a central processing unit (CPU), or 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. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0074] The memory 31 may be an internal storage unit of the terminal device 3, such as a hard disk or memory of the terminal device 3. The memory 31 may also be an external storage device of the terminal device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the terminal device 3. The memory 31 is used to store the computer program and other programs and data required by the roaming control device. The memory 31 may also be used to temporarily store data that has been output or is to be output.

[0075] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0076] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0077] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0078] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0079] An embodiment of the present invention provides a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0080] If the integrated unit 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 this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiments can be implemented. Among them, 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 at least include: any entity or device that can carry the computer program code to the camera device / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0081] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0082] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0083] In the embodiments provided by the present invention, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0084] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed over multiple network units.

[0085] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0086] It should also be understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0087] As used in the present specification and the appended claims, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to monitoring, depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is monitored" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is monitored" or "in response to monitoring [described condition or event]", depending on the context.

[0088] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0089] References to "one embodiment" or "some embodiments" etc. described in the present specification mean that one or more embodiments of the present invention include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0090] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A smart campus OA office data interaction method, characterized in that: The smart campus OA office data interaction method is applied to an OA system, wherein the OA system includes a cloud server and an OA client, and the smart campus OA office data interaction method includes: The cloud server receives the data extraction request sent by the OA client, and extracts the original data corresponding to the data extraction request; The cloud server matches a preset key set corresponding to the sensitivity level according to the sensitivity level of the original data; The cloud server divides the original data into fixed sizes to obtain multiple original data blocks; The cloud server extracts the odd-numbered original data block set and the even-numbered original data block set respectively according to the order of the multiple original data blocks in the original data; The cloud server encrypts the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set; The cloud server sends the first ciphertext and the second ciphertext to the OA client in sequence.

2. The smart campus OA office data interaction method according to claim 1, characterized in that: Before the cloud server matches the preset key set corresponding to the sensitivity level according to the sensitivity level of the original data, the method further includes: Randomly generate initial keys corresponding to different sensitivity levels, and send the initial keys to the OA client; the OA client is used to generate a key set according to the initial keys; Splitting the initial key to obtain multiple first subkeys; Performing cyclic shift processing on the multiple first subkeys to obtain multiple second subkeys; The key set is obtained by performing convolution calculation based on the multiple first subkeys and the multiple second subkeys.

3. The smart campus OA office data interaction method according to claim 2, characterized in that: The step of performing convolution calculation based on the multiple first subkeys and the multiple second subkeys to obtain the key set comprises: Based on the multiple first subkeys, construct a first convolution kernel; Arranging the plurality of first subkeys according to preset positions to form a first data matrix; Performing convolution processing on the plurality of the first data matrices respectively through the first convolution kernel to obtain a plurality of first target keys; Based on the multiple second subkeys, construct a second convolution kernel; Arranging the plurality of second sub-keys according to preset positions to form a second data matrix; Performing convolution processing on the plurality of second data matrices respectively by using the second convolution kernel to obtain a plurality of second target keys; A plurality of first target keys and a plurality of second target keys are used as the key set.

4. The smart campus OA office data interaction method according to claim 3, characterized in that: The step of constructing a first convolution kernel based on the multiple first subkeys includes: Extracting the first two characters and the last two characters of the plurality of first subkeys respectively; Constructing the first two characters and the last two characters corresponding to each of the first subkeys into a first convolution kernel according to a preset element position; Correspondingly, the step of constructing a second convolution kernel based on the multiple second subkeys includes: extracting first two characters and last two characters of a plurality of said second subkeys respectively; The first two characters and the last two characters corresponding to each of the plurality of the second subkeys are constructed into a second convolution kernel according to preset element positions.

5. The smart campus OA office data interaction method according to claim 1, characterized in that: The cloud server encrypts the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set, comprising: Based on a plurality of first target keys in the key set, encrypting the odd-numbered original data block set in order to obtain a first ciphertext corresponding to the odd-numbered original data block set; Based on the multiple second target keys in the key set, the even-numbered original data block set is encrypted in sequence to obtain a second ciphertext corresponding to the even-numbered original data block set.

6. The smart campus OA office data interaction method according to claim 1, characterized in that: The step of the cloud server sending the first ciphertext and the second ciphertext to the OA client in sequence includes: The first ciphertext, the sequence number corresponding to the sensitivity level, the original data sequence number, the sequence number corresponding to the first ciphertext, and the number of ciphertexts are respectively encapsulated into a data packet to obtain a plurality of first data packets corresponding to the first ciphertext; the sequence number corresponding to the first ciphertext is used to instruct the OA client to combine the original data blocks corresponding to the first ciphertext in sequence to obtain the original data; The second ciphertext, the sequence number corresponding to the sensitivity level, the original data sequence number, the sequence number corresponding to the second ciphertext, and the number of ciphertexts are respectively encapsulated into a data packet to obtain a plurality of second data packets corresponding to the second ciphertext; the sequence number corresponding to the second ciphertext is used to instruct the OA client to combine the original data blocks corresponding to the second ciphertext in sequence to obtain the original data; Send multiple first data packets and multiple second data packets to the OA client in sequence.

7. The smart campus OA office data interaction method according to claim 6, characterized in that: After the step of sending the plurality of first data packets and the plurality of second data packets to the OA client in sequence, the method further includes: The OA client receives a plurality of first data packets and a plurality of second data packets sent by the cloud server; If the number of the plurality of first data packets and the plurality of second data packets is consistent with the number of ciphertexts, the OA client matches the corresponding sensitivity level according to the sequence number corresponding to the sensitivity level; The OA client matches the initial key corresponding to the sensitivity level and generates a key set according to the initial key; The OA client decrypts the first ciphertext and the second ciphertext according to the key set, the sequence number corresponding to the first ciphertext, and the sequence number corresponding to the second ciphertext to obtain a plurality of original data blocks; The OA client combines the multiple original data blocks according to the sequence numbers corresponding to the first ciphertexts and the sequence numbers corresponding to the second ciphertexts to obtain the original data.

8. An intelligent campus OA office data interaction device, characterized in that: The smart campus OA office data interaction device comprises: A first extraction unit, configured to receive, by the cloud server, a data extraction request sent by the OA client, and extract original data corresponding to the data extraction request; A matching unit, configured for the cloud server to match a preset key set corresponding to the sensitivity level according to the sensitivity level of the original data; A segmentation unit, used for the cloud server to segment the original data according to a fixed size to obtain a plurality of original data blocks; A second extraction unit is used for the cloud server to extract the odd-numbered original data block set and the even-numbered original data block set respectively according to the order of the multiple original data blocks in the original data; An encryption unit is used for the cloud server to encrypt the odd-numbered original data block set and the even-numbered original data block set respectively by using the key set to obtain a first ciphertext corresponding to the odd-numbered original data block set and a second ciphertext corresponding to the even-numbered original data block set; The sending unit is used for the cloud server to send the first ciphertext and the second ciphertext to the OA client in sequence.

9. A terminal device, characterized in that: The terminal device includes: a memory, a processor, and a smart campus OA office data interaction program stored in the memory and executable on the processor, wherein the smart campus OA office data interaction program is configured to implement the steps in the smart campus OA office data interaction method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the steps in the smart campus OA office data interaction method as described in any one of claims 1 to 7 are implemented.

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