A Method for Remote Secure Transmission of Data in a Commodity Supply Chain Platform

Abstract

The present invention relates to the technical field of data transmission, and proposes a method for remotely and securely transmitting data for a commodity supply chain platform, including: collecting static data and dynamic data during the transmission process of the commodity supply chain platform; determining the static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue during the transmission process; dividing out the abnormal static data fluctuation eigenvalue from the static data fluctuation eigenvalue. If the static data fluctuation eigenvalue is an abnormal static data fluctuation eigenvalue, determine the key according to the static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue during the transmission process. If not, determine the key according to the dynamic data fluctuation eigenvalues of all transmission processes from the previous transmission process corresponding to the abnormal static data fluctuation eigenvalue to the target transmission process; realize the remote and secure transmission of the data of the commodity supply chain platform according to the key. The purpose of the present invention is to improve the stability of the operation of the commodity supply chain platform when using TLS / SSL encryption for data transmission.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and particularly relates to a method for remotely and securely transmitting data for a commodity supply chain platform. Background Art

[0002] The commodity supply chain platform connects manufacturers, suppliers, distributors, and retailers, and realizes the highly integrated and optimized flow of information, logistics, and funds through digital means. To ensure the efficient cooperation among all links of the supply chain, the security and integrity of data transmission in the commodity supply chain platform are particularly crucial. TLS is the Transport Layer Security protocol, and SSL is the Secure Sockets Layer protocol. TLS and SSL are encryption protocols used to protect the security of network communication. In the prior art, TLS / SSL encryption is often used to reduce the probability of data being tampered with during data transmission, and to ensure the security, accuracy, and normal operation of the supply chain platform.

[0003] The commodity supply chain platform needs to process a large amount of real-time data. When using TLS / SSL encryption for data transmission, high-frequency key updates are required. Frequent handshake negotiations will increase the overhead, and the huge key space will also cause a serious storage burden, affecting the stability of the operation of the commodity supply chain platform. Therefore, on the premise of ensuring the security and integrity of data transmission, there is an urgent need for a more efficient data transmission method to ensure the stable operation of the commodity supply chain platform. Summary of the Invention

[0004] The present invention provides a method for remotely and securely transmitting data for a commodity supply chain platform to solve the problem that the high-frequency key updates when using TLS / SSL encryption for data transmission affect the stability of the operation of the commodity supply chain platform. The specific technical solutions adopted are as follows:

[0005] An embodiment of the present invention provides a method for remotely and securely transmitting data for a commodity supply chain platform, and the method includes the following steps:

[0006] Collect static data and dynamic data of each transmission process of the commodity supply chain platform;

[0007] Record any one transmission process as the target transmission process, and determine the static data fluctuation characteristic value of the target transmission process according to the differences between the values of the same type of static data of the target transmission process and all previous transmission processes, and the differences between the change trends of different types of static data, and obtain the dynamic data fluctuation characteristic value of the target transmission process;

[0008] Determine whether the static data fluctuation eigenvalue is an abnormal static data fluctuation eigenvalue. If so, determine the key of the target transmission process according to the static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue of the target transmission process. If not, determine the key of the target transmission process according to the dynamic data fluctuation eigenvalues of all transmission processes from the transmission process corresponding to the abnormal static data fluctuation eigenvalue to the target transmission process during the transmission process before the target transmission process; implement the remote secure transmission of the data of the commodity supply chain platform during the target transmission process according to the key of the target transmission process.

[0009] Further, the specific method for determining the static data fluctuation eigenvalue of the target transmission process according to the differences between the values of the same type of static data in the target transmission process and all previous transmission processes, and the differences between the change trends of different types of static data includes:

[0010] Arrange the same type of static data in the target transmission process and all previous transmission processes in the order of transmission, and obtain the static data transmission sequence of the same type of static data in the static data of the target transmission process; obtain the first-order difference sequence of the static data transmission sequence, and use the polynomial fitting method to perform polynomial fitting on the first-order difference sequence of the static data transmission sequence to obtain the fitting curve of the static data transmission sequence;

[0011] Determine the static data fluctuation eigenvalue of the target transmission process according to the differences between the data included in the static data transmission sequence of the same type of static data in the target transmission process, the similarity of the static data transmission sequences of all different types of static data in the target transmission process, and the differences between the fitting curves of the static data transmission sequences of all different types of static data in the target transmission process.

[0012] Further, the specific method for determining the static data fluctuation eigenvalue of the target transmission process according to the differences between the data included in the static data transmission sequence of the same type of static data in the target transmission process, the similarity of the static data transmission sequences of all different types of static data in the target transmission process, and the differences between the fitting curves of the static data transmission sequences of all different types of static data in the target transmission process includes:

[0013] Record the variance of all the values included in the static data transmission sequence of the same type of static data in the target transmission process as the volatility of the same type of static data in the target transmission process, and record the cumulative sum of the volatilities of all the same type of static data in the target transmission process as the static data volatility of the target transmission process;

[0014] In the static data transfer sequence of all static data of the same type during the target transfer process, the cumulative sum of the similarities between every two static data transfer sequences is denoted as the static data fluctuation similarity of the target transfer process;

[0015] In the fitting curves of all types of static data during the target transfer process, the cumulative sum of the absolute values of the differences between the integral areas of every two fitting curves is denoted as the static data trend similarity of the target transfer process;

[0016] Based on the static data volatility, static data trend similarity, and static data fluctuation similarity of the target transfer process, determine the static data fluctuation eigenvalue of the target transfer process.

[0017] Furthermore, the specific method for determining the static data fluctuation eigenvalue of the target transfer process based on the static data volatility, static data trend similarity, and static data fluctuation similarity of the target transfer process is as follows:

[0018] The ratio of the product of the static data volatility and the static data trend similarity of the target transfer process to the static data fluctuation similarity is denoted as the static data fluctuation eigenvalue of the target transfer process.

[0019] Furthermore, the method for determining the abnormal static data fluctuation eigenvalue is as follows:

[0020] Obtain the division threshold of the static data fluctuation eigenvalues of all transfer processes in the commodity supply chain platform, and denote the static data fluctuation eigenvalues greater than the division threshold as abnormal static data fluctuation eigenvalues.

[0021] Furthermore, the specific method for determining the key of the target transfer process based on the static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue of the target transfer process if the static data fluctuation eigenvalue of the target transfer process is an abnormal static data fluctuation eigenvalue is as follows:

[0022] When the static data fluctuation eigenvalue of the target transfer process is an abnormal static data fluctuation eigenvalue, the exclusive OR operation result of the numerical values represented in binary of the static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue of the target transfer process is denoted as the key influence factor of the target transfer process;

[0023] Based on the key influence factor of the target transfer process, determine the key of the target transfer process.

[0024] Furthermore, the specific method for determining the key of the target transfer process based on the key influence factor of the target transfer process is as follows:

[0025] Use the key influence factor of the target transfer process as the key of the target transfer process.

[0026] Further, if not, according to the dynamic data fluctuation eigenvalues of all the transmission processes from the transmission process corresponding to the abnormal static data fluctuation eigenvalue to the target transmission process during the transmission process before the target transmission process, the method for determining the key of the target transmission process specifically includes:

[0027] When the static data fluctuation eigenvalue of the target transmission process is not the abnormal static data fluctuation eigenvalue, the transmission process with the static data fluctuation eigenvalue being the abnormal static data fluctuation eigenvalue and being closest to the target transmission process in time during the transmission process before the target transmission process is recorded as the comparison transmission process;

[0028] The exclusive OR operation result of the numerical values represented in binary of the dynamic data fluctuation eigenvalues of all the transmission processes from the comparison transmission process to the target transmission process is recorded as the first operation result of the target transmission process. The first operation result of the target transmission process is used as the value of the independent variable of the hash function, and the function value corresponding to the hash function is calculated and recorded as the key influence factor of the target transmission process;

[0029] Use an encryption algorithm to obtain the initial key of the target transmission process, and combine it with the key influence factor of the target transmission process to determine the key of the target transmission process.

[0030] Further, the method for using an encryption algorithm to obtain the initial key of the target transmission process and combining it with the key influence factor of the target transmission process to determine the key of the target transmission process specifically includes:

[0031] The concatenation operation result of the key of the target transmission process obtained by using TLS / SSL encryption and the key influence factor of the target transmission process is used as the key of the target transmission process.

[0032] Further, the method for realizing the remote secure transmission of the data of the commodity supply chain platform during the target transmission process according to the key of the target transmission process specifically includes:

[0033] According to the key of the target transmission process, use the TLS / SSL encryption algorithm to encrypt the static data and dynamic data of the target transmission process to obtain the encrypted ciphertext, and perform data transmission on the ciphertext of the target transmission process to realize the remote secure transmission of the data of the commodity supply chain platform during the target transmission process.

[0034] The beneficial effects of the present invention are:

[0035] This application first considers that static data represents the basic information of the transaction data transmitted by both parties of data transmission, while dynamic data has high timeliness. Evaluate the degree of change of the static data and dynamic data in the target transmission process, obtain the static data fluctuation eigenvalue and dynamic data fluctuation eigenvalue of the target transmission process, and divide the abnormal static data fluctuation eigenvalue from the static data fluctuation eigenvalues according to the static data fluctuation eigenvalues of all transmission processes. The transmission process corresponding to the abnormal static data fluctuation eigenvalue is the transmission process in which the static data has changed significantly. When the static data fluctuation eigenvalue of the target transmission process is an abnormal static data fluctuation eigenvalue, the basic information of the data provider in the data transmission process has changed greatly, and the next adjacent transmission process of the target transmission process needs to obtain a new original key through a handshake again. Therefore, determine the key of the target transmission process according to the static data fluctuation eigenvalue and dynamic data fluctuation eigenvalue of the target transmission process to ensure the security of the commodity supply chain platform. When the static data fluctuation eigenvalue of the target transmission process is not an abnormal static data fluctuation eigenvalue, the basic information of the transaction data transmitted by the transmission process corresponding to the static data fluctuation eigenvalue between two abnormal static data fluctuation eigenvalues has high similarity. Therefore, determine the key of the target transmission process according to the dynamic data fluctuation eigenvalues of all transmission processes from the transmission process corresponding to the abnormal static data fluctuation eigenvalue to the target transmission process in the transmission process before the target transmission process. In this process, only need to calculate the exclusive OR operation result of the binary values of the dynamic data fluctuation eigenvalues of the transmission process to realize the verification of the identity, avoid the overhead caused by re-handshaking to confirm the identity of the other party, and at the same time, ensure that there is a large difference before and after the key update, thereby ensuring the effectiveness of the key update and the security of the commodity supply chain platform. Finally, realize the remote secure transmission of the data of the commodity supply chain platform in the target transmission process according to the key of the target transmission process, solve the problem that the high-frequency key update affects the stability of the operation of the commodity supply chain platform when using TLS / SSL encryption for data transmission, and improve the stability of the operation of the commodity supply chain platform. Brief Description of the Drawings

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0037] Figure 1 Schematic flowchart of a method for remote secure transmission of data for a commodity supply chain platform provided by an embodiment of the present invention;

[0038] Figure 2 Flowchart for obtaining the key in the transmission process provided by an embodiment of the present invention. Detailed implementation manners

[0039] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0040] Please refer to Figure 1 , which shows a flowchart of a method for remotely and securely transmitting data for a commodity supply chain platform provided by an embodiment of the present invention. The method includes the following steps:

[0041] Step S001: Collect the static data and dynamic data of each transmission process of the commodity supply chain platform.

[0042] The data of the commodity supply chain platform includes two categories: static data and dynamic data. The static data includes production - end information such as production enterprises, commodity specification information such as size and material, and supplier information; the dynamic data includes order information, warehousing information, logistics information, and transaction flow records.

[0043] Among them, all static data and dynamic data are converted into numerical forms for storage.

[0044] So far, the static data and dynamic data of each transmission process of the commodity supply chain platform are obtained.

[0045] Step S002: Denote any one transmission process as the target transmission process. Determine the static data fluctuation eigenvalue of the target transmission process based on the differences between the values of the same type of static data in the target transmission process and all previous transmission processes, as well as the differences between the change trends of different types of static data. Obtain the dynamic data fluctuation eigenvalue of the target transmission process. Without changing the TLS / SSL encryption algorithm process, the key itself does not have the function of self-revocation, so permissions have a certain transitivity. That is, after a user has obtained the historical data permissions of another user at least once, the permissions can be passed to the updated data. Therefore, during the data transmission process in the supply chain platform, if other personnel succeed in an attack or obtain a legitimate permission once, they can still obtain the subsequent transmitted data based on the obtained permissions, and all subsequent data transmissions are insecure. The TLS / SSL encryption algorithm usually uses the method of updating the key regularly to solve this problem. For example, the commodity supply chain platform updates the key in each transmission process, but frequent key updates will lead to frequent handshakes, affecting the operation efficiency of the commodity supply chain platform. Therefore, in order to ensure the operation efficiency of the commodity supply chain platform under the premise of data security, it is necessary to determine the timing of key updates according to the stability and security of the data itself, reduce the overhead of handshake negotiation, and maintain the security and stability of the commodity supply chain platform.

[0046] Static data represents the basic information of the transaction data transmitted between the two parties of data transmission. Static data can reflect the production and sales situation of users from the side, while dynamic data has high timeliness, and dynamic data reflects the change in the volume of transactions. Therefore, when using the supply chain platform for data transmission, static data has high stability. When the static data remains stable or has small changes, the two parties of data transmission have shared relatively important basic information, and the change in dynamic data only indicates the transaction volume fluctuation based on these basic information. At this time, a relatively simple update method can be adopted, that is, the updated key can be obtained by simply calculating according to the change in dynamic data to improve the efficiency of key update. However, when the static data changes relatively greatly, the production and sales of the data provider change greatly, indicating that the historical basic information obtained by the two parties of data transmission before is no longer sufficient to reflect the production and sales situation of the data provider at the current moment, the historical basic information obtained by the data receiver is inaccurate, and the basic information of the data provider also changes greatly. For the data provider, a relatively complex key update is required to prevent the data receiver who has interacted with itself before from still being able to directly obtain or relatively easily break through the data transmission process and illegally obtain new basic information.

[0047] Denote any one transmission process as the target transmission process, and determine the fitting curve of each type of static data in the target transmission process respectively according to the values of the same type of static data in the target transmission process and all previous transmission processes.

[0048] Arrange the same type of static data in the target transmission process and all previous transmission processes in the order of transmission, obtain the static data transmission sequence of the same type of static data in the target transmission process, obtain the first-order difference sequence of the static data transmission sequence, and use the polynomial fitting method to perform polynomial fitting on the first-order difference sequence of the static data transmission sequence to obtain the fitting curve of the static data transmission sequence. The independent variable corresponding to the fitting curve is the number determined by natural numbers starting from 1 in the order of each transmission process. Denote the fitting curve as the fitting curve of the corresponding type of static data of the corresponding target transmission process.

[0049] Thus, the fitting curves of all types of static data in the target transmission process can be obtained.

[0050] Among them, calculating the first-order difference sequence of the sequence and performing polynomial fitting on the sequence using the polynomial fitting method are both well-known techniques and will not be elaborated here.

[0051] Determine the static data fluctuation characteristic value of the target transmission process according to the differences between the data included in the static data transmission sequence of the same type of static data in the target transmission process, the similarity of the static data transmission sequences of all different types of static data in the target transmission process, and the differences between the fitting curves of the static data transmission sequences of all different types of static data in the target transmission process.

[0052] Preferably, as an embodiment of the present application, denote the variance of all the values included in the static data transmission sequence of the same type of static data in the target transmission process as the volatility of the same type of static data in the target transmission process, and denote the sum of the volatilities of all the same type of static data in the target transmission process as the static data volatility of the target transmission process; denote the sum of the similarities of every two static data transmission sequences in all the static data transmission sequences of the same type of static data in the target transmission process as the static data fluctuation similarity of the target transmission process; denote the sum of the absolute values of the differences between the integral areas of every two fitting curves in the fitting curves of all types of static data in the target transmission process in the target transmission process as the static data trend similarity of the target transmission process, where the lower limit of the integral of the integral area of the fitting curve is 0 and the upper limit is the number corresponding to the target transmission process; denote the ratio of the product of the static data volatility and the static data trend similarity to the static data fluctuation similarity of the target transmission process as the static data fluctuation characteristic value of the target transmission process.

[0053] Among them, in this embodiment, the Pearson correlation coefficient is selected to evaluate the similarity of two static data transmission sequences. As other implementation manners, on the basis of achieving the purpose of measuring the similarity of two static data transmission sequences, the implementer can use other methods in the prior art, such as cosine similarity, Spearman correlation coefficient, etc., to obtain the similarity of two static data transmission sequences, and this application does not make special restrictions; on the basis of determining the lower integration limit and the upper integration limit of the fitting curve, calculating the difference in the integration areas of the two fitting curves is a well-known technology and will not be elaborated; calculating the variance of all the values included in the static data transmission sequence is a well-known technology and will not be elaborated.

[0054] Using the difference in the integration areas of the fitting curves to measure the similarity between the change trends of different types of static data in the static data of the target transmission process can more accurately measure the difference in the change trends of different types of static data.

[0055] When the difference between the values of the same type of static data in the target transmission process and all the previous transmission processes is smaller, and the similarity between the change trends of different types of static data is larger and the difference is smaller, the change in the static data is smaller. At this time, the static data fluctuation eigenvalue of the target transmission process is smaller.

[0056] According to the method of obtaining the static data fluctuation eigenvalue of the target transmission process based on the static data of the target transmission process and all the previous transmission processes, obtain the dynamic data fluctuation eigenvalue of the target transmission process based on the dynamic data of the target transmission process and all the previous transmission processes.

[0057] The static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue of the target transmission process respectively evaluate the change degrees of the static data and the dynamic data of the target transmission process. Whether to update the secret key and the way to update the secret key can be determined according to the change degrees of the static data and the dynamic data of the target transmission process.

[0058] The static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue of any transmission process can be obtained according to the same method.

[0059] So far, the static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue of each transmission process of the commodity supply chain platform are obtained.

[0060] Step S003: Determine whether the static data fluctuation eigenvalue is an abnormal static data fluctuation eigenvalue. If so, determine the key of the target transmission process based on the static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue of the target transmission process. If not, determine the key of the target transmission process based on the dynamic data fluctuation eigenvalues of all transmission processes from the transmission process corresponding to the abnormal static data fluctuation eigenvalue to the target transmission process during the transmission process before the target transmission process; implement the remote secure transmission of the data of the commodity supply chain platform during the target transmission process according to the key of the target transmission process. Process the static data fluctuation eigenvalues of all transmission processes of the commodity supply chain platform using the Otsu method to obtain a division threshold, and record the static data fluctuation eigenvalues greater than the division threshold as abnormal static data fluctuation eigenvalues.

[0061] Among them, the abnormal static data fluctuation eigenvalue is the static data fluctuation eigenvalue corresponding to the static data with a relatively large degree of change. The static data of each transmission process corresponding to the static data fluctuation eigenvalue between two abnormal static data fluctuation eigenvalues has not changed significantly, and the influencing factor for adjusting the key, that is, the key influencing factor, can be determined according to the static data fluctuation eigenvalues of each transmission process between the two abnormal static data fluctuation eigenvalues.

[0062] When the static data fluctuation eigenvalue of the target transmission process is an abnormal static data fluctuation eigenvalue, record the exclusive OR operation result of the numerical values represented in binary of the static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue of the target transmission process as the key influencing factor of the target transmission process; use the key influencing factor of the target transmission process as the key of the target transmission process.

[0063] The basic information of the transaction data transmitted during the transmission process corresponding to the abnormal static data fluctuation eigenvalue has changed significantly. Therefore, the key influencing factor of the target transmission process is jointly constructed based on the dynamic data and the static data to ensure a large difference before and after the key update, thereby ensuring the effectiveness of the key update.

[0064] It can be understood that when the static data fluctuation eigenvalue of the target transmission process is an abnormal static data fluctuation eigenvalue, the basic information of the data provider in the data transmission process has changed significantly. If the old key is still used, the security of the commodity supply chain platform may be threatened. Therefore, the next adjacent transmission process of the target transmission process needs to obtain a new original key through a handshake again. At the same time, in order to minimize the handshake negotiation in other transmission processes that are relatively similar to the static data of the target transmission process after the target transmission process, the key of the target transmission process is required.

[0065] When the static data fluctuation eigenvalue of the target transmission process is not an abnormal static data fluctuation eigenvalue, among the transmission processes before the target transmission process, the transmission process with the static data fluctuation eigenvalue being an abnormal static data fluctuation eigenvalue and being closest to the target transmission process in terms of time is denoted as the comparison transmission process. The exclusive OR operation result of the numerical values represented in binary of the dynamic data fluctuation eigenvalues of all the transmission processes from the comparison transmission process to the target transmission process is denoted as the first operation result of the target transmission process. The value of the first operation result of the target transmission process is used as the value of the independent variable of the hash function, and the function value corresponding to the hash function is calculated. The calculated function value is denoted as the key influence factor of the target transmission process; the initial key of the target transmission process is obtained using the TLS / SSL encryption algorithm, and in combination with the key influence factor of the target transmission process, the key of the target transmission process is determined. Specifically, the concatenation operation result of the initial key of the target transmission process and the key influence factor is used as the key of the target transmission process.

[0066] Representing the numerical value in binary, calculating the exclusive OR operation result of the two numerical values, and the hash function are all well-known technologies and will not be elaborated further; among them, the concatenation operation is a well-known operation method of cryptographic concatenation operation and will not be elaborated further. For example, the concatenation operation result of 1 and 0 is 10.

[0067] There is a high similarity in the basic information of the transaction data transmitted by the transmission process corresponding to the static data fluctuation eigenvalue between two abnormal static data fluctuation eigenvalues. Therefore, constructing the key influence factor of the target transmission process based on the dynamic data can ensure a large difference before and after the key update, thereby ensuring the effectiveness of the key update. At the same time, constructing the key influence factor of the target transmission process based on the dynamic data and obtaining the key of the target transmission process only requires calculating the exclusive OR operation result of the binary values of the dynamic data fluctuation eigenvalues of all the transmission processes from the comparison transmission process to the target transmission process, which can achieve the verification of the identity, avoid the overhead caused by re-handshaking to confirm the identity of the other party, and at the same time ensure the security of the commodity supply chain platform. Further, jointly determining the key of the target transmission process based on the abnormal static data fluctuation eigenvalue and the dynamic data fluctuation eigenvalue helps to achieve the verification of the user identity and avoid losses caused by man-in-the-middle attacks.

[0068] The flowchart for obtaining the key of the transmission process is as Figure 2 shown.

[0069] In summary, since the specific method of key update is determined by the change of the data itself, there is no need for the commodity supply chain platform to update the key every time data is transmitted, reducing the burden on the commodity supply chain platform. The key determination method provided in this embodiment can achieve more efficient data transmission while ensuring the security and integrity of data transmission, and ensure the stable operation of the entire commodity supply chain platform.

[0070] Use the key of the target transmission process as the key of the TLS / SSL encryption algorithm, encrypt the static data and dynamic data of the target transmission process using the TLS / SSL encryption algorithm to obtain the encrypted ciphertext, and perform data transmission on the ciphertext of the target transmission process to achieve the remote secure transmission of the data of the commodity supply chain platform during the target transmission process.

[0071] Among them, using the TLS / SSL encryption algorithm to encrypt static data and dynamic data is a well-known technology and will not be elaborated here.

[0072] According to the same method, the key of any transmission process can be obtained, and based on the key of the transmission process, the remote secure transmission of the data of the commodity supply chain platform during any transmission process can be achieved.

[0073] Thus far, the remote secure transmission of the data of the commodity supply chain platform is achieved.

[0074] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for remote secure data transmission for a commodity supply chain platform, characterized in that: The method comprises the following steps: Collect static and dynamic data of each transmission process of the commodity supply chain platform; Record any transmission process as the target transmission process, arrange the same type of static data of the target transmission process and all previous transmission processes in the order of transmission, and obtain a static data transmission sequence; perform polynomial fitting on the first-order difference sequence of the static data transmission sequence to obtain a fitting curve of the static data transmission sequence; record the variance of all values ​​contained in the static data transmission sequence of the same type of static data in the target transmission process as the volatility of the same type of static data in the target transmission process, and record the cumulative sum of the volatility of all the same type of static data in the target transmission process as the static data volatility of the target transmission process; record the cumulative sum of the similarities of every two static data transmission sequences in the static data transmission sequence of all the same type of static data in the target transmission process as the static data volatility similarity of the target transmission process; record the cumulative sum of the absolute values ​​of the difference between the integral areas of every two fitting curves of all types of static data in the target transmission process in the fitting curve of the target transmission process as the static data trend similarity of the target transmission process; record the ratio of the product of the static data volatility of the target transmission process and the static data trend similarity to the static data fluctuation similarity as the static data fluctuation characteristic value of the target transmission process; Determine whether the static data fluctuation characteristic value is an abnormal static data fluctuation characteristic value. If so, determine the key of the target transmission process based on the static data fluctuation characteristic value and the dynamic data fluctuation characteristic value of the target transmission process. If not, determine the key of the target transmission process based on the dynamic data fluctuation characteristic values ​​of all transmission processes from the transmission process corresponding to the abnormal static data fluctuation characteristic value to the target transmission process in the transmission process before the target transmission process. Based on the key of the target transmission process, realize the remote secure transmission of data of the commodity supply chain platform in the target transmission process.

2. A method for remote secure data transmission for a commodity supply chain platform according to claim 1, characterized in that: The method for determining the abnormal static data fluctuation characteristic value is: The division threshold of the static data fluctuation characteristic value of all transmission processes of the commodity supply chain platform is obtained, and the static data fluctuation characteristic value greater than the division threshold is recorded as an abnormal static data fluctuation characteristic value.

3. A method for remote secure data transmission for a commodity supply chain platform according to claim 1, characterized in that: The method of judging whether the static data fluctuation characteristic value is an abnormal static data fluctuation characteristic value, and if so, determining the key of the target transmission process according to the static data fluctuation characteristic value and the dynamic data fluctuation characteristic value of the target transmission process, includes the following specific methods: When the static data fluctuation characteristic value of the target transmission process is an abnormal static data fluctuation characteristic value, the XOR operation result of the static data fluctuation characteristic value and the dynamic data fluctuation characteristic value of the target transmission process respectively expressed in binary is recorded as the key influencing factor of the target transmission process; The key of the target transmission process is determined according to the key influencing factor of the target transmission process.

4. A method for remote secure data transmission for a commodity supply chain platform according to claim 3, characterized in that: The key of the target transmission process is determined according to the key influencing factor of the target transmission process, and the specific method includes: The key influencing factor of the target transmission process is used as the key of the target transmission process.

5. The method for remote secure data transmission for a commodity supply chain platform according to claim 1, characterized in that: If not, the key of the target transmission process is determined according to the dynamic data fluctuation characteristic values ​​of all transmission processes from the transmission process corresponding to the abnormal static data fluctuation characteristic value in the transmission process before the target transmission process to the target transmission process, including the specific method of: When the static data fluctuation characteristic value of the target transmission process is not the abnormal static data fluctuation characteristic value, the transmission process before the target transmission process, in which the static data fluctuation characteristic value is the abnormal static data fluctuation characteristic value and the transmission process closest in time to the target transmission process, is recorded as the comparison transmission process; The XOR operation result of the dynamic data fluctuation characteristic values ​​of all transmission processes when comparing the transmission process to the target transmission process, which are respectively expressed in binary, is recorded as the first operation result of the target transmission process, the first operation result of the target transmission process is used as the value of the independent variable of the hash function, the function value corresponding to the hash function is calculated, and the calculated function value is recorded as the key influencing factor of the target transmission process; An encryption algorithm is used to obtain the initial key of the target transmission process, and the key of the target transmission process is determined in combination with the key influencing factor of the target transmission process.

6. A method for remote secure data transmission for a commodity supply chain platform according to claim 5, characterized in that: The method of using an encryption algorithm to obtain an initial key of the target transmission process and combining the key influencing factor of the target transmission process to determine the key of the target transmission process includes the following specific methods: The result of the cascade operation of the key of the target transmission process obtained by using TLS / SSL encryption and the key influencing factor of the target transmission process is used as the key of the target transmission process.

7. A method for remote secure data transmission for a commodity supply chain platform according to claim 1, characterized in that: The method of realizing remote secure transmission of data of the commodity supply chain platform in the target transmission process according to the key of the target transmission process includes the following specific methods: According to the key of the target transmission process, the static data and dynamic data of the target transmission process are encrypted using the TLS / SSL encryption algorithm, the encrypted ciphertext is obtained, and the ciphertext of the target transmission process is transmitted data, thereby realizing the remote and secure transmission of the data of the commodity supply chain platform in the target transmission process.

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