Cross-national energy transaction risk assessment method and system
By acquiring and analyzing transaction data in cross-border energy transactions, evaluating the degree of interference and security credibility of transaction data in different time processes, the problem of inability to accurately evaluate data security risks in the existing technology is solved, and more accurate Data security risk assessment.
Patent Information
- Application Number
- CN202411167632.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-23
- Publication Date
- 2025-02-14
AI Technical Summary
The existing technology cannot effectively combine the ability of transaction data under different categories within different time processes to withstand external interference, resulting in the inability to accurately conduct data security risk assessment.
By obtaining the transaction volume data, transaction price data and transaction order response time data under the number of transactions, comprehensively analyze the sensitive situation of the data being affected by the outside world, obtain the degree of interference, and analyze the overall fluctuation and stability of the number of transactions, and obtain the transaction Data security credibility is finally classified and security assessment is carried out based on security credibility.
By combining the ability of transaction data to withstand external interference under different categories within different time processes, the impact of external interference on the judgment of transaction data security is reduced and the accuracy of data security risk assessment is improved.
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Figure CN119444222A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of transaction data processing, and in particular to a method and system for assessing cross-border energy transaction risks. Background Art
[0002] In the context of global economic integration, international companies need to conduct cross-border energy transactions. However, due to the many factors that need to be considered in the process of cross-border energy transactions, it is considered to be a relatively difficult transaction activity. In actual situations, companies may encounter external network attacks in all aspects of the transaction process, which may cause problems with the value of transaction data during the transaction process. Therefore, it is necessary to evaluate the data security risks of transaction data during energy transactions to ensure the reliability of the corresponding energy supply during the transaction process.
[0003] In the process of cross-border energy transactions, different categories of transaction data have different sensitivities to external network attacks, resulting in different levels of data security for energy transactions in different time processes. However, existing technologies cannot effectively combine the ability of transaction data of different categories in different time processes to withstand external interference, and therefore cannot accurately conduct data security risk assessments. Summary of the invention
[0004] The present invention provides a method and system for assessing the risk of cross-border energy transactions to solve the existing problem that the ability of transaction data of different categories in different time processes to withstand external interference cannot be effectively combined, and data security risk assessment cannot be accurately performed.
[0005] A method and system for assessing risk of transnational energy transactions of the present invention adopts the following technical solutions:
[0006] The present invention proposes a method for assessing the risk of transnational energy transactions, which comprises the following steps:
[0007] Obtain transaction volume data, transaction price data, and transaction order response time data for a certain number of transactions;
[0008] Based on the changes in the transaction volume data, transaction price data, and transaction order response time data for each transaction, the sensitivity of the data to external influences is comprehensively analyzed to obtain the degree of interference for each transaction;
[0009] Analyze the fluctuation and stability of the overall interference level of transaction times, and obtain the security and reliability of transaction data at each transaction time;
[0010] According to the security credibility of transaction data, all transaction times are graded to obtain several security level categories; according to the security level categories, security assessment is carried out.
[0011] Preferably, the method for obtaining the interference degree is:
[0012] Record any number of transactions as the target number of transactions;
[0013] Analyze the difference in trading volume distribution between the target trading times and the previous trading times to obtain trading volume sensitivity;
[0014] Analyze the difference in transaction price distribution between the target transaction times and the previous transaction times to obtain the transaction price sensitivity;
[0015] Analyze the difference in transaction order response time distribution between the target transaction number and the previous transaction number to obtain the transaction order response time sensitivity;
[0016] The degree of interference is obtained based on the transaction volume sensitivity, transaction price sensitivity, and transaction order response time sensitivity.
[0017] Preferably, the method for obtaining the transaction volume sensitivity is:
[0018] The transaction volume sensitivity is obtained by calculating the difference in transaction volume ratio between the target transaction number and the transaction volume data of the entire previous transaction number; the transaction volume sensitivity is positively correlated with the difference in transaction volume ratio.
[0019] Preferably, the method for obtaining the transaction price sensitivity is:
[0020] The transaction price sensitivity is obtained by calculating the difference in transaction price ratio between the target transaction number and the transaction price data of the previous transaction number as a whole; the transaction price sensitivity is positively correlated with the difference in transaction price ratio.
[0021] Preferably, the method for obtaining the transaction order response time sensitivity is:
[0022] The transaction order response time sensitivity is obtained by calculating the difference in transaction order response time ratio between the target transaction number and the transaction order response time data of the entire previous transaction number; the transaction order response time sensitivity is positively correlated with the difference in transaction order response time ratio.
[0023] Preferably, the method for obtaining the security credibility of the transaction data is:
[0024] Record any transaction number as the first target transaction number; analyze the distribution of interference levels between the first target transaction number and previous different transaction numbers to obtain the local interference stability of the first target transaction number;
[0025] Obtaining a comparison value of the interference degree between the first target transaction number and the previous transaction number as a whole;
[0026] According to the local interference stability and the interference degree comparison value, the transaction data security credibility under the first target transaction number is obtained; the transaction data security credibility is negatively correlated with the local interference stability and positively correlated with the interference degree comparison value.
[0027] Preferably, the method for acquiring the local interference stability is:
[0028] Before the first target transaction number, the local change difference of the interference degree between different transaction numbers and the first target transaction number is compared to obtain the local interference stability of the first target transaction number; the local interference stability is negatively correlated with the local change difference.
[0029] Preferably, after calculating the security credibility of the transaction data, the method further includes:
[0030] Normalize the security and credibility of transaction data.
[0031] Preferably, the method for obtaining the security level category is:
[0032] All transaction times are clustered to obtain several clusters; according to the differences in security credibility of transaction data between different transaction times in different clusters, several security level categories are obtained.
[0033] The present invention also proposes a transnational energy transaction risk assessment system, comprising a memory and a processor, wherein the processor executes a computer program stored in the memory to implement the steps of the above-mentioned transnational energy transaction risk assessment method.
[0034] The beneficial effects of the technical solution of the present invention are: based on the changes in transaction volume data, transaction price data and transaction order response time data under each transaction number, the sensitivity of the data to external influences is comprehensively analyzed to obtain the degree of interference under each transaction number; wherein the degree of interference is used to describe the degree to which the transaction data is fluctuated by external factors, so that the influence of external factors on the transaction data is clearer; the fluctuation stability of the overall interference degree of the transaction number is analyzed to obtain the security credibility of the transaction data under each transaction number; wherein the security credibility of the transaction data is used to describe the ability of the transaction data to withstand external network attacks, and effectively considers the impact of external network attacks on the overall transaction data; finally, according to the security credibility of the transaction data, all transaction times are graded to obtain several security level categories; the present invention reduces the interference of external interference on the judgment of the security of transaction data by combining the ability of transaction data under different categories in different time processes to withstand external interference, and improves the accuracy of data security risk assessment. BRIEF DESCRIPTION OF THE DRAWINGS
[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.
[0036] Figure 1 The present invention is a flowchart of the steps of a method for risk assessment of cross-border energy transactions. DETAILED DESCRIPTION
[0037] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a method and system for risk assessment of cross-border energy transactions proposed by the present invention, its specific implementation, structure, features and effects, in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.
[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
[0039] The specific scheme of a cross-border energy transaction risk assessment method and system provided by the present invention is described in detail below with reference to the accompanying drawings.
[0040] See also Figure 1 , which shows a flowchart of a method for risk assessment of cross-border energy transactions provided by an embodiment of the present invention, the method comprising the following steps:
[0041] Step S001: Obtain transaction volume data, transaction price data, and transaction order response time data for a certain number of transactions.
[0042] It should be noted that in the process of cross-border energy transactions, due to the different sensitivities of different categories of transaction data to external network attacks, the data security levels of energy transactions in different time processes are different. The existing technology cannot effectively combine the ability of transaction data of different categories in different time processes to withstand external interference, and cannot accurately conduct data security risk assessments.
[0043] In a specific implementation of an embodiment of the present invention, a method for obtaining transaction volume data, transaction price data and transaction order response time data is as follows: obtaining three types of transaction data, namely, transaction volume data, transaction price data and transaction order response time data for several transaction times from an energy transaction database.
[0044] It should be noted that the transaction order response time data refers to the time difference between the transaction contract signing time and the energy transportation start time for each transaction.
[0045] It is particularly noted that this embodiment is described by taking 20 transactions as an example, wherein the number of transactions may be determined according to specific implementation circumstances.
[0046] So far, the transaction volume data, transaction price data and transaction order response time data under several transaction times are obtained through the above method.
[0047] Step S002: Based on the changes in the transaction volume data, transaction price data and transaction order response time data for each transaction, a comprehensive analysis is performed on the sensitivity of the data to external influences to obtain the degree of interference for each transaction.
[0048] It should be noted that every time an enterprise conducts a transaction, if there is any numerical change in the transaction volume data, transaction price data and transaction order response time data corresponding to the number of transactions, it will directly affect the final transaction result in the energy trading process; this means that transaction volume data, transaction price data and transaction order response time data are more important than other types of transaction data, such as the number of participants in the transaction contract between the two parties. Therefore, based on the changes in transaction volume data, transaction price data and transaction order response time data at each transaction number, we can comprehensively analyze the sensitivity of the data to external influences and obtain the degree of interference at each transaction number.
[0049] Preferably, in some implementations of the embodiments of the present invention, the method for obtaining the interference degree is: record any transaction number as the target transaction number; analyze the difference in transaction volume distribution between the target transaction number and the previous transaction number to obtain the transaction volume sensitivity; analyze the difference in transaction price distribution between the target transaction number and the previous transaction number to obtain the transaction price sensitivity; analyze the difference in transaction order response time distribution between the target transaction number and the previous transaction number to obtain the transaction order response time sensitivity; obtain the interference degree according to the transaction volume sensitivity, transaction price sensitivity, and transaction order response time sensitivity. The specific process is:
[0050] 1. Get volume sensitivity.
[0051] It should be noted that, for the transaction volume data under any transaction number, the transaction volume data under the previous transaction number as a whole can measure the historical supply volume when the two enterprises conduct energy transactions in the corresponding energy transaction history record; at the same time, because the development of transactions is a process of gradual technological advancement, the overall historical supply volume will also show a certain trend distribution; if the previous historical supply volume under the current transaction number is larger, it means that the supply volume under the current transaction number should be relatively larger, which is in line with the distribution trend of the corresponding data of energy supply quantity; if the previous historical supply volume under the current transaction number is larger, the supply volume under the current transaction number is relatively too small or too large, which means that the transaction volume data is more likely to be affected by external factors and produce unstable numerical changes, reflecting that the transaction volume data is more sensitive.
[0052] The method for obtaining the transaction volume sensitivity is as follows: the transaction volume sensitivity is obtained by calculating the difference in transaction volume ratio between the target transaction number and the transaction volume data of the previous transaction number; the transaction volume sensitivity is positively correlated with the difference in transaction volume ratio. As an example, the transaction volume sensitivity of the target transaction number can be calculated by the following formula:
[0053]
[0054] Where R represents the transaction volume sensitivity of the target transaction number; A represents the transaction volume data of the target transaction number; Represents the mean of the transaction volume data under all transaction times before the target transaction time; | | represents the removal of absolute value; nom() represents the linear normalization function.
[0055] It should be noted that Indicates the difference in transaction volume proportion; if the transaction volume sensitivity is greater, it means that the transaction volume data is more likely to be affected by external factors and produce unstable numerical changes, reflecting that the transaction volume data is more sensitive. The number 1 in this embodiment is used as a measurement indicator for the transaction volume comparison and cannot be changed to other values.
[0056] 2. Obtain transaction price sensitivity.
[0057] It should be noted that for the transaction price data under any transaction number, the transaction price data under the previous transaction number as a whole can measure the historical transaction amount when the two enterprises conduct energy transactions in the corresponding energy transaction history record; when multiple transactions are actually carried out continuously, the historical transaction amount is one of the important judgment standard data that can intuitively reflect the transaction results. The change of its value will not only directly affect the transaction results, but also indirectly affect other transaction data; therefore, the larger the proportion of the transaction number to the previous historical transaction amount, the more likely it is that the transaction price data under the transaction number is abnormal, the greater the possibility of being attacked by external networks, the greater the interference to other transaction data, and the more sensitive the transaction price data.
[0058] The method for obtaining the transaction price sensitivity is: the transaction price sensitivity is obtained by calculating the difference in transaction price ratio between the target transaction number and the transaction price data of the previous transaction number; the transaction price sensitivity is positively correlated with the difference in transaction price ratio. As an example, the transaction price sensitivity of the target transaction number can be calculated by the following formula:
[0059]
[0060] Where RL represents the transaction price sensitivity of the target transaction number; B represents the transaction price data of the target transaction number; Represents the average of transaction price data for all transaction times before the target transaction time; || indicates removing the absolute value.
[0061] It should be noted that Indicates the difference in transaction price proportion; if the transaction price sensitivity is greater, it means that the transaction price data under the target transaction number is more likely to be abnormal, the possibility of being attacked by external networks is greater, the interference to other transaction data is greater, and the transaction price data is more sensitive. The number 1 in this embodiment is used as a measurement indicator for the transaction price comparison and cannot be changed to other values.
[0062] 3. Obtain transaction order response time sensitivity.
[0063] It should be noted that for the transaction order response time data under any transaction number, the overall transaction order response time data under the previous transaction number can measure the on-site response speed of the enterprise in fulfilling the transaction contract and delivering energy within the corresponding energy transaction history record; usually, in the process of continuous transactions, the enterprise needs to ensure that the overall energy landing speed of each transaction is stable, so as to ensure that the subsequent transactions between the two parties can continue to be effectively executed; if the proportion of the transaction number to the overall transaction order response time data before is larger, it means that the energy delivery situation under the transaction number is more unsatisfactory, the corresponding transaction order response time data is more likely to be abnormal, and the possibility of being attacked by external network is greater, reflecting that the transaction order response time data is more sensitive.
[0064] The method for obtaining the transaction order response time data sensitivity is as follows: the transaction order response time sensitivity is obtained by calculating the difference in transaction order response time ratio between the target transaction number and the transaction order response time data of the previous transaction number as a whole; the transaction order response time sensitivity is positively correlated with the difference in transaction order response time ratio. As an example, the transaction order response time sensitivity of the target transaction number can be calculated by the following formula:
[0065]
[0066] Where RL represents the transaction order response time sensitivity of the target transaction number; C represents the transaction order response time data of the target transaction number; Represents the mean of transaction order response time data under all transaction times before the target transaction time; || indicates removing the absolute value.
[0067] It should be noted that Indicates the difference in transaction order response time; if the transaction order response time sensitivity is greater, the energy delivery situation under the transaction number is more unsatisfactory, the corresponding transaction order response time data is more likely to be abnormal, and the possibility of being attacked by external networks is greater, reflecting that the transaction order response time data is more sensitive. The number 1 in this embodiment is used as a measurement indicator for the comparison of transaction response speed and cannot be changed to other values.
[0068] 4. Obtain the degree of interference based on transaction volume sensitivity, transaction price sensitivity, and transaction order response time sensitivity.
[0069] The product of the transaction volume sensitivity, transaction price sensitivity and transaction order response time sensitivity of the target transaction number is taken as the interference degree of the target transaction number.
[0070] It is particularly noted that, in this embodiment, the interference degree under the first transaction number is not considered by default.
[0071] Furthermore, the degree of interference for each transaction is obtained.
[0072] At this point, the interference degree for each transaction is obtained through the above method.
[0073] Step S003: Analyze the fluctuation stability of the overall interference degree of the transaction times, and obtain the security reliability of the transaction data under each transaction time.
[0074] It should be noted that, in actual practice, the final transaction results under different transaction times will affect each other, thereby affecting the determination results of the security status of transaction data under different transaction times; therefore, the security credibility of transaction data under each transaction time can be obtained through the fluctuation stability of the overall interference degree of the transaction times; the greater the security credibility of transaction data, the higher the security of transaction data under that transaction time.
[0075] Preferably, in some implementations of the embodiments of the present invention, the method for obtaining the security credibility of transaction data is as follows: record any transaction number as the first target transaction number; analyze the distribution of the interference degree between the first target transaction number and the previous different transaction numbers to obtain the local interference stability of the first target transaction number; obtain the interference degree comparison value between the first target transaction number and the previous transaction number as a whole; obtain the security credibility of transaction data under the first target transaction number based on the local interference stability and the interference degree comparison value; the security credibility of transaction data is negatively correlated with the local interference stability and positively correlated with the interference degree comparison value. The specific process is:
[0076] It should be noted that for the first target transaction number, the data security of the first target transaction number needs to be comprehensively analyzed based on the degree of interference under the previous transaction number; however, in the transaction numbers before the first target transaction number, as time goes by, the security impact of different transaction numbers on the transaction number will also change. Therefore, the distribution of the degree of interference between the first target transaction number and the previous different transaction numbers can be analyzed to obtain the local interference stability of the first target transaction number; the greater the local interference stability, the greater the data security under the first target transaction number is affected by the previous transaction number.
[0077] The method for obtaining the local interference stability is as follows: before the first target transaction number, the local change difference of the interference degree between different transaction numbers and the first target transaction number is compared to obtain the local interference stability of the first target transaction number; the local interference stability is negatively correlated with the local change difference. As an example, the local interference stability under the first target transaction number can be calculated by the following formula:
[0078]
[0079] Where Q represents the local interference stability under the first target transaction number; N represents the number of all transactions before the first target transaction number; K represents the interference degree under the first target transaction number; K n Indicates the degree of interference at the nth transaction number before the first target transaction number; Δm n represents the number of transactions between the nth transaction number before the first target transaction number and the first target transaction number; μ represents a preset hyperparameter. In this embodiment, μ=1 is preset to prevent the denominator from being 0; | | represents an absolute value; exp[ ] represents an exponential function with a natural constant as the base. In this embodiment, the exp[-x] model is used to present the inverse proportional relationship and normalization processing. x is the input of the model. The implementer can select the inverse proportional function and normalization function according to the actual situation.
[0080] It should be noted that Indicates the difference in local changes; if the local interference stability under the first target transaction number is greater, it means that the data security under the first target transaction number is more affected by the previous transaction number.
[0081] Furthermore, in an implementation of the embodiment of the present invention, the average of the interference levels under all transaction times before the first target transaction time is used as the historical interference average of the first target transaction time; the ratio of the interference level of the first target transaction time to the historical interference average is used as the interference level comparison value of the first target transaction time; the normalized value of the ratio between the interference level comparison value of the first target transaction time and the local interference stability of the first target transaction time is used as the transaction data security credibility under the first target transaction time. The transaction data security credibility under each transaction time is obtained.
[0082] It is particularly noted that, in this embodiment, the normalization operation is performed by default using the norm() linear normalization function; in addition, in this embodiment, the security credibility of the transaction data under the first transaction number is not considered by default.
[0083] At this point, the security reliability of the transaction data under each transaction number is obtained through the above method.
[0084] Step S004: According to the security credibility of the transaction data, all transaction times are graded to obtain several security level categories; and security assessment is performed according to the security level categories.
[0085] It should be noted that the security credibility of transaction data reflects the pressure that transaction data with the corresponding number of transactions can withstand from external network attacks. Under normal circumstances, enterprises need to keep transaction data stable within an allowable fluctuation range to ensure the normal operation of energy trading activities. Therefore, all transaction times can be graded according to the security credibility of transaction data to obtain several security level categories. Security assessments can be conducted based on the security level categories.
[0086] Preferably, in some implementations of the present invention, the method for obtaining the security level category is: clustering all transaction times to obtain a number of clusters; and obtaining a number of security level categories according to the difference in security credibility of transaction data between different transaction times in different clusters. The specific process is:
[0087] The absolute value of the difference in the security credibility of transaction data between different transaction times is used as the distance metric, and all transaction times are clustered to obtain several clusters; any cluster is recorded as the target cluster, and the level of the target cluster is obtained according to the comparative difference in the security credibility of transaction data between the target cluster and other clusters. The process of clustering according to the distance metric is a well-known content of the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) density-based clustering algorithm, in which the minimum number of samples in the DBSCAN density-based clustering algorithm is preset to 4, and the neighborhood radius is preset to 3, which will not be repeated in this embodiment. As an example, the level of the target cluster can be calculated by the following formula:
[0088]
[0089] Where W represents the level of the target cluster; D1 represents the maximum value of the security credibility of the transaction data of all transaction times in the target cluster; D2 represents the minimum value of the security credibility of the transaction data of all transaction times in the target cluster; V represents the number of all clusters except the target cluster; Represents the mean value of the security credibility of transaction data of all transaction times in the target cluster; It represents the mean value of the security credibility of transaction data of all transactions in the vth cluster except the target cluster.
[0090] It should be noted that, if the level of the target cluster is higher, it means that the data security of the corresponding transaction data within the target cluster is higher, reflecting that the corresponding transaction data within the target cluster is more likely to fluctuate within the allowable security data variation range.
[0091] Furthermore, the levels of all clusters are obtained; the sequence obtained by arranging all clusters in descending order according to the levels is recorded as a security level sequence; and each cluster in the security level sequence is recorded as a security level category.
[0092] Preferably, in an implementation of the embodiment of the present invention, the specific process of security assessment is: taking any security level category as an example, taking the normalized value of the product of the mean value of the security credibility of the transaction data of all transaction times in the security level category and the level of the security level category as the security index of the security level category; presetting a security index threshold T1, if the security index of the security level category is less than T1, the transaction data of all transaction times in the security level category is recorded as high-risk data; if the security index of the security level category is greater than or equal to T1, the transaction data of all transaction times in the security level category is recorded as risk-free data. This embodiment is described by taking T1=0.6 as an example, and this embodiment is not specifically limited, and T1 can be determined according to the specific implementation situation.
[0093] Through the above steps, the risk assessment method based on cross-border energy transactions is completed.
[0094] Another embodiment of the present invention provides a cross-border energy transaction risk assessment system, the system comprising a memory and a processor, and when the processor executes the computer program stored in the memory, the above method steps S001 to S004 are performed.
[0095] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.
Claims
1. A method for assessing risk in transnational energy transactions, characterized in that: The method comprises the following steps: Obtain transaction volume data, transaction price data, and transaction order response time data for a certain number of transactions; Based on the changes in the transaction volume data, transaction price data, and transaction order response time data for each transaction, the sensitivity of the data to external influences is comprehensively analyzed to obtain the degree of interference for each transaction; Analyze the fluctuation and stability of the overall interference degree of the number of transactions, and obtain the security and reliability of the transaction data under each transaction number; According to the security credibility of transaction data, all transaction times are graded to obtain several security level categories; according to the security level categories, security assessment is carried out.
2. A method for assessing risk of transnational energy transactions according to claim 1, characterized in that: The method for obtaining the interference degree is: Record any number of transactions as the target number of transactions; Analyze the difference in trading volume distribution between the target trading times and the previous trading times to obtain trading volume sensitivity; Analyze the difference in transaction price distribution between the target transaction times and the previous transaction times to obtain the transaction price sensitivity; Analyze the difference in transaction order response time distribution between the target transaction number and the previous transaction number to obtain the transaction order response time sensitivity; The degree of interference is obtained based on the transaction volume sensitivity, transaction price sensitivity, and transaction order response time sensitivity.
3. A method for assessing risk of transnational energy transactions according to claim 2, characterized in that: The method for obtaining the transaction volume sensitivity is: The transaction volume sensitivity is obtained by calculating the difference in transaction volume ratio between the target transaction number and the transaction volume data of the entire previous transaction number; the transaction volume sensitivity is positively correlated with the difference in transaction volume ratio.
4. A method for assessing risk of transnational energy transactions according to claim 2, characterized in that: The method for obtaining the transaction price sensitivity is: The transaction price sensitivity is obtained by calculating the difference in transaction price ratio between the target transaction number and the transaction price data of the previous transaction number as a whole; the transaction price sensitivity is positively correlated with the difference in transaction price ratio.
5. According to claim 2, a method for assessing risk of transnational energy transactions is characterized in that: The method for obtaining the transaction order response time sensitivity is: The transaction order response time sensitivity is obtained by calculating the difference in transaction order response time ratio between the target transaction number and the transaction order response time data of the entire previous transaction number; the transaction order response time sensitivity is positively correlated with the difference in transaction order response time ratio.
6. A method for assessing risk of transnational energy transactions according to claim 1, characterized in that: The method for obtaining the security credibility of the transaction data is: Record any transaction number as the first target transaction number; analyze the distribution of interference levels between the first target transaction number and previous different transaction numbers to obtain the local interference stability of the first target transaction number; Obtaining a comparison value of the interference degree between the first target transaction number and the previous transaction number as a whole; According to the local interference stability and the interference degree comparison value, the transaction data security credibility under the first target transaction number is obtained; the transaction data security credibility is negatively correlated with the local interference stability and positively correlated with the interference degree comparison value.
7. A method for assessing risk of transnational energy transactions according to claim 6, characterized in that: The method for obtaining the local disturbance stability is: Before the first target transaction number, the local change difference of the interference degree between different transaction numbers and the first target transaction number is compared to obtain the local interference stability of the first target transaction number; the local interference stability is negatively correlated with the local change difference.
8. A method for assessing risk of transnational energy transactions according to claim 1, characterized in that: After calculating the security credibility of transaction data, it also includes: Normalize the security and credibility of transaction data.
9. A method for assessing risk of transnational energy transactions according to claim 1, characterized in that: The method for obtaining the security level category is: All transaction times are clustered to obtain several clusters; according to the differences in security credibility of transaction data between different transaction times in different clusters, several security level categories are obtained.
10. A transnational energy transaction risk assessment system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of a method for risk assessment of cross-border energy transactions as described in any one of claims 1 to 9 are implemented.