Privacy information security protection method and system for power transaction platform

Abstract

The application relates to the technical field of network security, in particular to a private information security protection method and system for a power transaction platform. The method first determines the attack possibility of the power transaction platform suffering from a DDOS attack; in combination with the attack possibility, the historical transaction of a transaction combination and the periodic characteristics of transaction power, determines a protection attention factor of the transaction combination; according to the encryption condition of the transaction combination when the transaction content is encrypted, determines the transaction privacy degree of the transaction combination; in combination with the protection attention factor and the transaction privacy degree, determines the request threshold demand index of the transaction combination; according to the request threshold demand index, adjusts the preset rated QPS threshold value to obtain the adaptive QPS threshold value of the transaction combination; and according to the adaptive QPS threshold value of each transaction combination, carries out the security protection measure on the transaction request of the power transaction platform. The application improves the security protection efficiency of the private information of the power transaction platform.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of network security, in particular to a privacy information security protection method and system for a power transaction platform. BACKGROUND

[0002] The power transaction platform supports the coordinated operation of new energy such as wind power and photovoltaic and traditional power sources, promotes the transformation of energy structure, and at the same time provides a fair trading place for power generation enterprises, power selling companies and power users, promotes the market competition of the power generation side and the demand side, and further releases the vitality and potential of the power market.

[0003] Because the power transaction platform has a large number of power resources and privacy information, the platform is often subjected to malicious attacks such as DDOS attacks by illegal hackers. The DDOS attack on the power transaction platform will cause the server traffic of the platform to surge, and further cause the server performance to collapse. The traditional protection method is to limit the QPS threshold of each transaction combination in real time through a Web application firewall. The QPS threshold is the maximum number of requests that a single transaction combination can handle in a unit of time, thereby improving the ability of the power transaction platform to resist hacker attacks and further improving the security protection level of the privacy information of the transaction parties.

[0004] However, the traditional Wed application firewall technology selects the QPS threshold parameter of each transaction combination in real time according to the platform traffic. If the real-time platform traffic is higher, the QPS threshold of each transaction combination is set lower. However, this traditional QPS threshold selection method does not consider the performance impact caused by hacker DDOS attacks on the platform, such as the degradation of server bandwidth and transaction response delay, resulting in poor adaptability of the QPS threshold. At the same time, in the actual power transaction scene, the privacy information encryption requirements of each transaction party are different, which further leads to insufficient precision of the QPS threshold setting for each transaction party of the platform, and reduces the security protection efficiency of the privacy information of the power transaction platform. SUMMARY

[0005] In order to solve the technical problem of low adaptability in traditional QPS threshold selection, the purpose of the present application is to provide a privacy information security protection method and system for a power transaction platform, and the technical solution adopted is as follows:

[0006] In the first aspect, the present application embodiment provides a privacy information security protection method for a power transaction platform, which comprises:

[0007] analyzing the real-time transaction demand and short-term transaction response delay of the power transaction platform to determine the attack possibility of the power transaction platform subjected to DDOS attacks;

[0008] Determine a protection emphasis factor of the transaction combination according to the attack possibility, historical transactions of the transaction combination and periodic characteristics of transaction electricity;

[0009] Determine a transaction privacy degree of the transaction combination according to encryption of the transaction combination to transaction content during transaction process; and determine a request threshold demand index of the transaction combination according to the protection emphasis factor and the transaction privacy degree;

[0010] Adjust a preset rated QPS threshold according to the request threshold demand index to obtain an adaptive QPS threshold of the transaction combination; and perform security protection measures on transaction requests of the power transaction platform according to the adaptive QPS threshold of each transaction combination.

[0011] Further, the real-time transaction demand and short-term transaction response delay of the power transaction platform are analyzed to determine the attack possibility of the power transaction platform under DDOS attack, including:

[0012] Determine a performance weakness presentation degree of the power transaction platform according to short-term change trend of IP access volume of the power transaction platform, bandwidth degradation characteristics and remaining memory proportion;

[0013] Determine the attack possibility of the power transaction platform under DDOS attack according to the performance weakness presentation degree and the short-term transaction response delay.

[0014] Further, the acquisition method of the short-term change trend of the IP access volume of the power transaction platform is:

[0015] Obtain a ratio of IP access volume of the power transaction platform at the current time to maximum IP access volume as a first change trend;

[0016] Determine a second change trend according to change of IP access volume in a short-term reference time range corresponding to the current time;

[0017] Obtain the short-term change trend by combining the first change trend and the second change trend; wherein the first change trend and the second change trend are positively correlated with the short-term change trend.

[0018] Further, the acquisition method of the bandwidth degradation characteristics of the power transaction platform is:

[0019] Determine an initial degradation characteristic according to change of bandwidth in a short-term reference time range corresponding to the current time;

[0020] Determine the bandwidth degradation characteristics by combining real-time bandwidth of the power transaction platform and the initial degradation characteristic; wherein the real-time bandwidth and the bandwidth degradation characteristics are negatively correlated, and the initial degradation characteristic and the bandwidth degradation characteristics are positively correlated.

[0021] Further, the combination of the attack possibility, the historical transaction of the transaction combination and the period characteristic of the transaction power are used to determine a protection importance factor of the transaction combination, including:

[0022] According to the historical transaction of the transaction combination and the period characteristic of the transaction power, the power transaction confidence of the transaction combination is determined.

[0023] The protection importance factor of the transaction combination is obtained by combining the attack possibility and the power transaction confidence.

[0024] Further, the power transaction confidence of the transaction combination is determined according to the historical transaction of the transaction combination and the period characteristic of the transaction power, including:

[0025] The time period characteristic value of the historical transaction of the transaction combination is determined; the time period characteristic value represents the time interval error of the transaction.

[0026] The power period characteristic value of the historical transaction of the transaction combination is determined; the power period characteristic value represents the transaction power error of the transaction.

[0027] The power transaction confidence of the transaction combination is determined by combining the time period characteristic value and the power period characteristic value; the time period characteristic value and the power period characteristic value are negatively correlated with the power transaction confidence.

[0028] Further, the transaction privacy degree of the transaction combination is determined according to the encryption condition when the transaction combination encrypts the transaction content during the transaction process, including:

[0029] The transaction privacy degree of the transaction combination is determined by the encryption level and the number of encrypted data packets when the transaction combination encrypts the transaction content during the transaction process.

[0030] Further, the request threshold demand index of the transaction combination is determined by combining the protection importance factor and the transaction privacy degree, including:

[0031] The ratio of the protection importance factor and the transaction privacy degree is taken as the request threshold demand index of the transaction combination.

[0032] Further, the adaptive QPS threshold of the transaction combination is obtained by adjusting the preset rated QPS threshold according to the request threshold demand index, including:

[0033] The adjustment coefficient is determined by comparing the request threshold demand index and the standard request threshold demand index.

[0034] The preset rated QPS threshold is adjusted by taking the adjustment coefficient as a weight to obtain the adaptive QPS threshold of the transaction combination.

[0035] In a second aspect, a privacy information security protection system for a power transaction platform is provided, and the system comprises the following modules:

[0036] An attack analysis module is configured to analyze real-time transaction demand and short-term transaction response delay of the power transaction platform, and determine an attack possibility of the power transaction platform under a DDOS attack.

[0037] A protection analysis module is configured to determine a protection importance factor of a transaction combination in combination with the attack possibility, historical transactions of the transaction combination, and periodic characteristics of transaction power.

[0038] A privacy analysis module is configured to determine a transaction privacy degree of the transaction combination according to encryption of the transaction combination to transaction content during a transaction process, and determine a request threshold demand index of the transaction combination in combination with the protection importance factor and the transaction privacy degree.

[0039] An adaptive adjustment module is configured to adjust a preset rated QPS threshold according to the request threshold demand index to obtain an adaptive QPS threshold of the transaction combination, and perform a security protection measure on a transaction request of the power transaction platform according to the adaptive QPS threshold of each transaction combination.

[0040] In a third aspect, an electronic device is provided, which comprises a memory and a processor, the memory stores executable code, and the processor executes the executable code to implement the embodiments of each possible implementation of the first aspect.

[0041] In a fourth aspect, a computer program product is provided, which comprises computer program code, and when the computer program code is executed on a computer, the computer executes the method in the first aspect or any one of the possible implementation manners of the first aspect.

[0042] In a fifth aspect, a computer readable storage medium is provided, which stores a computer program, and when the computer program is executed in a computer, the computer executes the embodiments of each possible implementation of the first aspect.

[0043] The embodiments of the present application have at least the following beneficial effects:

[0044] The application proposes that the attack possibility of the power transaction platform under DDOS attack is obtained according to the performance analysis of the transaction changes in the short term of the power transaction platform and the short-term transaction response delay, and the historical transaction time interval characteristics and transaction power similar performance of a single transaction combination are analyzed, and then the real-time protection attention factor is obtained by combining the attack possibility, and the request threshold demand index is obtained by further analyzing the privacy information performance in the transaction content, compared with the traditional method, the application can combine the characteristics of hacker DDOS attack in the actual power transaction platform, the privacy information performance of the power transaction and the periodic characteristics in the historical data, realize the higher QPS threshold parameter of each transaction combination in real time, and improve the security protection efficiency of the privacy information of the power transaction platform. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art and the advantages thereof, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced as follows. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0046] Figure 1 The method flow chart of a privacy information security protection method for a power transaction platform provided by an embodiment of the present application;

[0047] Figure 2 The method flow chart of an attack possibility obtaining method provided by an embodiment of the present application;

[0048] Figure 3 The method flow chart of a protection attention factor obtaining method provided by an embodiment of the present application;

[0049] Figure 4 The system block diagram of a privacy information security protection system for a power transaction platform provided by an embodiment of the present application;

[0050] Figure 5 The structural schematic diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific implementation, structure, characteristics and effects of a privacy information security protection method and system for a power transaction platform according to the present application are described in detail as follows by combining the drawings and preferred embodiments.

[0052] In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0053] In the description of embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text only describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which means that there are three cases of A alone, A and B together, and B alone. In addition, in the description of embodiments of the present application, "multiple" means two or more than two.

[0054] Hereinafter, the terms "first", "second" are only for descriptive purposes, and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more features.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by a person skilled in the art of the technology to which the present application belongs.

[0056] The embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art can know that with the development of technology and the appearance of new scenes, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0057] The embodiments of the present application provide a specific implementation method of a privacy information security protection method and system for a power transaction platform. The method is suitable for the power transaction platform scene. The power transaction platform is the hub of power commodity circulation, and can be used for power supply and demand parties to realize power transaction, such as power transaction between power generation parties and power selling parties in the platform, power transaction between power selling parties and users, and power transaction between enterprise parties. The transaction parties enter the platform to realize power transaction through their respective IP addresses.

[0058] The specific scheme of the privacy information security protection method and system for the power transaction platform provided by the present application will be described below with reference to the accompanying drawings.

[0059] Please refer to Figure 1 which shows a step flowchart of a privacy information security protection method for a power transaction platform provided by an embodiment of the present application. The method includes the following steps:

[0060] Step S100, analyze the real-time transaction demand and short-term transaction response delay of the power transaction platform, and determine the attack possibility of the power transaction platform under DDOS attack.

[0061] The application firstly reads the real-time IP access amount, bandwidth and memory occupation information of the power transaction platform through the state parameter module, and the memory occupation information is the memory usage rate.

[0062] The historical transaction information of each transaction combination in the power transaction platform is read through the IP monitoring module, including the historical transaction time node, transaction power and transaction response duration.

[0063] The encryption level and the number of encrypted data packets of each data packet in the transaction content in each transaction combination of the power transaction platform during real-time transaction are read through the information monitoring module, and the number of encrypted data packets is referred to as the number of encrypted data packets.

[0064] The data read is preprocessed through data cleaning, and the preprocessed data is uploaded to the data acquisition system for subsequent analysis and use. The data read includes the IP access amount, bandwidth, memory usage rate, historical transaction time node, transaction power, transaction response duration, encryption level and number of encrypted data packets of the power transaction platform.

[0065] When the power transaction platform is attacked by DDOS, the hacker will forge multiple IP addresses and false transaction information to conduct centralized access attack with large amount of data on the platform server for a short time. Therefore, the step firstly obtains the traffic surge according to the IP access amount growth performance; further, a large number of access attacks cause the bandwidth stability of the platform server to decrease, and if the memory occupation of the platform server is poor at the same time, the real-time running performance of the platform is further weakened.

[0066] Therefore, after obtaining the data required for analysis of the application, the real-time transaction demand and short-term transaction response delay of the power transaction platform are analyzed to determine the attack possibility of the power transaction platform attacked by DDOS.

[0067] In the embodiment of the application, the step of obtaining the attack possibility of the power transaction platform attacked by DDOS is shown in Figure 2 , that is, the step S100 can be implemented by Figure 2 .

[0068] In step S110, the performance weakness degree of the power transaction platform is determined according to the short-term change trend of the IP access amount of the power transaction platform, the bandwidth degradation characteristics and the remaining memory occupation ratio.

[0069] Firstly, when the power transaction platform is attacked by hacker DDOS, the platform traffic will have explosive growth, so the IP access amount time series data of the platform in the short-term reference time range is obtained. In the embodiment of the application, the value of the short-term reference time range is 5s, and in other embodiments, the value can be adjusted by the implementer according to the actual situation.

[0070] The higher the value level of the IP access amount in the short-term reference time range and the greater the rising slope of the IP access amount, the greater the real-time traffic surge intensity of the platform.

[0071] The method for obtaining the short-term change trend of the IP access amount of the power transaction platform comprises the following steps: obtaining a ratio of the IP access amount of the power transaction platform at the current moment to the maximum IP access amount as a first change trend; determining a second change trend according to the change of the IP access amount in the short-term reference time range corresponding to the current moment; and obtaining the short-term change trend by combining the first change trend and the second change trend, wherein the first change trend and the second change trend are positively correlated with the short-term change trend.

[0072] In some embodiments, the IP access amount in the short-term reference time range corresponding to the current moment is linearly fitted by a least square fitting straight line method, and the slope of the fitted straight line is taken as the second change trend. When the slope of the fitted straight line is positive, it indicates that the IP access amount in the short-term reference time range is increasing, and the greater the slope, the greater the sudden change of the platform traffic.

[0073] In some embodiments, the product value of the first change trend and the second change trend is taken as the short-term change trend.

[0074] The calculation formula of the short-term change trend U is as follows: , wherein P is the IP access amount at the current moment; is the maximum IP access amount at the historical moment before the current moment; is the first change trend; is the second change trend.

[0075] Secondly, when the power transaction platform is subjected to a hacker DDOS attack or real-time real transaction demand is too high, bandwidth resources will be excessively consumed, resulting in a decrease in available bandwidth resources and poor bandwidth stability. Therefore, the bandwidth change of the power transaction platform is further analyzed to determine the bandwidth degradation feature of the power transaction platform.

[0076] The less the real-time bandwidth resources of the power transaction platform and the more significant the fluctuation feature of the bandwidth in the short term, the worse the performance of the bandwidth of the power transaction platform.

[0077] The method for obtaining the bandwidth degradation feature comprises the following steps: determining an initial degradation feature according to the change of the bandwidth in the short-term reference time range corresponding to the current moment; and determining the bandwidth degradation feature in combination with the real-time bandwidth of the power transaction platform and the initial degradation feature, wherein the real-time bandwidth and the bandwidth degradation feature are negatively correlated, and the initial degradation feature and the bandwidth degradation feature are positively correlated.

[0078] In some embodiments, the initial degradation feature is obtained by calculating the standard deviation of the bandwidth in the short-term reference time range corresponding to the current time.

[0079] In some embodiments, the ratio of the initial degradation feature of the power trading platform and the normalized value of the real-time bandwidth is taken as the initial degradation feature.

[0080] If the short-term change trend of the power trading platform is greater in real time, the bandwidth degradation feature is more significant, and the power trading platform is more likely to be in an abnormal state under DDOS hacker attack, more attention should be paid to security.

[0081] At the same time, the memory usage rate change of the power trading platform server is part of the server performance data troubleshooting. When troubleshooting DDOS attacks, if the memory usage rate abnormally increases, it may be that the attacker has sent a large number of false data query requests, causing the server to frequently allocate memory, so that the remaining memory space is insufficient.

[0082] Therefore, after obtaining the short-term change trend and the bandwidth degradation feature, the remaining memory percentage of the power trading platform is obtained.

[0083] Finally, the performance weakness degree of the power trading platform is determined in combination with the short-term change trend, the bandwidth degradation feature, and the remaining memory percentage. The short-term change trend, the bandwidth degradation feature, and the performance weakness degree are positively correlated, and the remaining memory percentage and the performance weakness degree are negatively correlated.

[0084] In some embodiments, the remaining memory percentage is the ratio of the real-time remaining memory size to the maximum memory size of the power trading platform.

[0085] In some embodiments, the product value of the short-term change trend and the bandwidth degradation feature is taken as the numerator, the remaining memory percentage is taken as the denominator, and the normalized value of the ratio of the numerator and the denominator is taken as the performance weakness degree. In the embodiment of the present application, if the remaining memory percentage is 1, that is, the memory is completely unoccupied, there is no need to perform subsequent adaptive adjustment of the QPS threshold value, and the transaction request of the power trading platform is directly protected according to the pre-set QPS threshold value. Therefore, there is no case of a meaningless ratio caused by a zero denominator.

[0086] When the short-term change trend and the bandwidth degradation feature are greater, the power trading platform is more likely to be in a performance abnormal state under DDOS attack, and if the real-time remaining memory percentage of the platform is more likely to be insufficient, the real-time performance of the power trading platform is worse, and more attention should be paid to security protection.

[0087] In step S120, the performance weakness presentation degree and the short-term transaction response delay degree are combined to determine the attack possibility of the power transaction platform under the DDOS attack.

[0088] When the power transaction platform is attacked by the DDOS hacker, the computing resources are excessively consumed, and at this time, the response of each power transaction of the platform in a short period of time is delayed.

[0089] For any moment, the response time of the power transaction completed at the moment is obtained, and the average value of the response time of each completed power transaction of the power transaction platform in a long-term reference time range corresponding to the moment is obtained as a reference response time. In the embodiment of the application, the long-term reference time range is 2 days.

[0090] The average value of the difference between the response time of each power transaction in a short-term reference time range and the reference response time is calculated as a short-term transaction response delay degree.

[0091] The greater the short-term transaction response delay degree is, the worse the response effect of the running performance of the power transaction platform in a short period of time on the transaction demand.

[0092] The performance weakness presentation degree and the short-term transaction response delay degree are combined to determine the attack possibility of the power transaction platform under the DDOS attack. The performance weakness presentation degree and the short-term transaction response delay degree are positively correlated with the attack possibility.

[0093] The greater the real-time performance weakness presentation degree of the power transaction platform is, the greater the possibility of being attacked by the hacker DDOS is. At the same time, the higher the short-term transaction response delay degree is, the greater the possibility of being attacked by the hacker DDOS in real time.

[0094] In some embodiments, the normalized value of the product value of the performance weakness presentation degree and the short-term transaction response delay degree is used as the attack possibility of the power transaction platform under the DDOS attack. It should be noted that the normalization method can adopt the maximum and minimum value normalization method.

[0095] In step S200, the attack possibility, the historical transaction of the transaction combination, and the periodic characteristics of the transaction power are combined to determine the protection attention factor of the transaction combination.

[0096] When the DDOS attack performance is stronger, the response delay of the transaction in a short period of time is aggravated, so the real-time attack possibility is obtained by combining the performance weakness presentation degree and the transaction response delay degree.

[0097] For the single pair transaction combination of the electricity trading platform, the transaction combination may be composed of transaction parties with real power supply and demand relationship, or composed of false transaction parties fabricated by hackers. The real transaction combination should have regular historical transaction performance compared with the false transaction combination in the DDOS attack, such as the periodicity of the electricity trading between the user and the power seller, and then the attack possibility of the electricity trading platform and the historical transaction performance get the protection attention factor.

[0098] Please refer to Figure 3 In some possible implementations, the above step S200 is implemented by the following process:

[0099] Step S210, according to the historical transaction and the periodicity of the transaction electricity of the transaction combination, the electricity trading confidence of the transaction combination is determined.

[0100] Because the conventional power consumer has periodicity, and then the transaction parties with cooperative relationship exist regularity such as monthly transaction when performing electricity trading on the platform, and the electricity difference is small each time, and the historical transaction of the real demand electricity trading parties should show periodicity in time sequence.

[0101] Therefore, for the current analyzed transaction combination of the electricity trading platform, the time interval of the historical transaction of the corresponding parties of the transaction combination and the transaction electricity corresponding to each transaction are obtained.

[0102] The time period characteristic value of the historical transaction of the transaction combination is determined; the time period characteristic value represents the time interval error of the historical transaction, and more specifically: the mean value of the time interval duration of the adjacent two historical transactions of the transaction combination is calculated as the reference time interval duration; the average value of the absolute value of the difference between the time interval duration of each adjacent two transactions of the transaction combination and the reference time interval duration is calculated as the time period characteristic value of the transaction combination.

[0103] The electricity quantity period characteristic value of the historical transaction of the transaction combination is determined; the electricity quantity period characteristic value represents the transaction electricity error of the historical transaction, and more specifically: the mean value of the transaction electricity of each historical transaction of the transaction combination is calculated as the reference transaction electricity; the average value of the absolute value of the difference between the transaction electricity of each transaction of the transaction combination and the reference transaction electricity is calculated as the electricity quantity period characteristic value of the transaction combination.

[0104] The electricity trading confidence of the transaction combination is determined in combination with the time period characteristic value and the electricity quantity period characteristic value; wherein the time period characteristic value and the electricity quantity period characteristic value are negatively correlated with the electricity trading confidence.

[0105] In some embodiments, the product value of the time period characteristic value and the power period characteristic value is negatively correlated normalized mapping, and the mapped result value is taken as the power transaction confidence. In the embodiment of the application, the product value can be negatively correlated normalized mapping by taking the natural constant as the base number and taking the inverse number of the product value of the time period characteristic value and the power period characteristic value as the index of the exponential function.

[0106] When the time period characteristic value and the power period characteristic value are smaller, the transaction periodicity of the corresponding transaction combination is more significant, which indicates that the transaction combination is more likely to maintain a stable long-term transaction cooperation relationship, and the authenticity of the transaction combination is higher, and correspondingly, the probability of the transaction combination being a false transaction combination fabricated by a hacker for DDOS attack is lower.

[0107] In step S220, the attack possibility and the power transaction confidence are combined to obtain a protection attention factor of the transaction combination.

[0108] When the power transaction confidence of the transaction combination currently analyzed by the power transaction platform is lower, it reflects that the possibility of the transaction combination being a virtual transaction combination generated by a hacker for DDOS attack is higher, and if the attack possibility of the power transaction platform is higher, it further indicates that the transaction combination currently analyzed needs to attract more attention for security protection, so the attack possibility and the power transaction confidence are used to calculate the protection attention factor of the transaction combination currently analyzed by the platform.

[0109] The attack possibility and the protection attention factor are positively correlated, and the power transaction confidence and the protection attention factor are negatively correlated.

[0110] In some embodiments, the normalized value of the ratio of the attack possibility and the power transaction confidence is taken as the protection attention factor.

[0111] In step S300, the transaction privacy degree of the transaction combination is determined according to the encryption condition of the transaction combination when the transaction content is encrypted in the transaction process, and the request threshold demand index of the transaction combination is determined in combination with the protection attention factor and the transaction privacy degree.

[0112] For a single pair of transaction combinations, the transaction parties share transaction files with the platform when they conduct power transactions, and the buying and selling parties self-selectively encrypt important contents in the transaction files to a certain level, so if the encryption level of the transaction content is higher and the encryption information accounts for a higher proportion in the encrypted content, it reflects that the transaction information privacy degree of the current transaction parties is higher, so the transaction privacy degree of the transaction combination can be determined by analyzing the encryption condition of the transaction combination when the transaction content is encrypted.

[0113] Determine the transaction privacy degree of the transaction combination through the encryption level and the number of encrypted data packets when the transaction content is encrypted by the transaction combination in the transaction process, and more specifically:

[0114] Obtain the proportion of the number of encrypted data packets in the transaction content corresponding to the current analyzed transaction combination of the power transaction platform, and obtain the average of the encryption level corresponding to the transaction content when each transaction is performed in the transaction combination as the average encryption level;

[0115] Determine the transaction privacy degree of the transaction combination in combination with the proportion of the number of encrypted data packets and the average encryption level, wherein the proportion of the number of encrypted data packets and the average encryption level are positively correlated with the transaction privacy degree.

[0116] The greater the transaction privacy degree, the stronger the information privacy of the transaction content corresponding to the current analyzed transaction combination.

[0117] If the transaction privacy degree of the current analyzed transaction combination is lower, and the protection attention factor of the transaction combination is greater, the protection degree of the transaction combination should be improved, so a lower QPS request threshold level should be applied to the transaction combination.

[0118] Determine the request threshold demand index of the transaction combination in combination with the protection attention factor and the transaction privacy degree, wherein the protection attention factor is positively correlated with the transaction request threshold demand index, and the transaction privacy degree is negatively correlated with the transaction request threshold demand index, and specifically: the normalized value of the ratio of the protection attention factor and the transaction privacy degree is taken as the request threshold demand index of the transaction combination.

[0119] Finally, obtain the request threshold demand index of all transaction combinations of the power transaction platform with real-time to-be-allocated QPS threshold.

[0120] Step S400, adjust the preset rated QPS threshold according to the request threshold demand index to obtain the adaptive QPS threshold of the transaction combination; and perform security protection measures on the transaction request of the power transaction platform according to the adaptive QPS threshold of each transaction combination.

[0121] Taking the real-time to-be-requested transaction combination of the power transaction platform as an example, the request threshold demand index corresponding to the transaction combination is obtained from step S300 , and then the average of the request threshold demand indexes of all transaction combinations of the power transaction platform in the past two days is calculated , and the preset rated QPS threshold is denoted as , it is to be noted that the preset rated QPS threshold is a rated value selected by an implementer, and in some embodiments, the preset rated QPS threshold can also be selected as the average value of the QPS thresholds of all transaction combinations in the past two days. .

[0122] If the real-time request threshold demand index of the transaction combination currently analyzed by the power transaction platform is higher than the historical overall value level, more transaction processing of the transaction combination can be allowed, and the QPS threshold of the transaction combination can be adaptively adjusted to be higher.

[0123] First, the request threshold demand index is compared with the standard request threshold demand index to determine an adjustment coefficient.

[0124] In some embodiments, the request threshold demand index corresponding to the easy combination is calculated , and the normalized value of the difference between the average value is calculated. The sum of the constant 1 and is used as the adjustment coefficient; wherein norm is a normalization function.

[0125] The preset rated QPS threshold is adjusted by using the adjustment coefficient as a weight to obtain the adaptive QPS threshold of the transaction combination.

[0126] In some embodiments, the product value of the adjustment coefficient and the preset rated QPS threshold is used as the adaptive QPS threshold of the transaction combination.

[0127] Finally, the transaction request of the power transaction platform is protected according to the adaptive QPS threshold of each transaction combination.

[0128] The preset threshold of the QPS threshold is set to 800, and if the adaptive QPS threshold of the transaction combination exceeds the preset threshold, the IP of the transaction combination exceeding the threshold is automatically triggered to flow.

[0129] If the adaptive QPS threshold of the transaction combination exceeds 1.5 times the preset threshold, the IP of the transaction combination is temporarily banned.

[0130] When the same IP triggers the interception rule 10 times within a short-term reference time range, an email or an SMS message is automatically sent to notify the security team.

[0131] Please refer to Figure 4 , Figure 4 A system block diagram of a privacy information security protection system for a power transaction platform is provided for the embodiments of the present application, and the system comprises:

[0132] An attack analysis module is configured to analyze real-time transaction demand and short-term transaction response delay of the power transaction platform, and determine attack possibility of the power transaction platform under a DDOS attack;

[0133] A protection analysis module is configured to determine a protection attention factor of the transaction combination based on the attack possibility, historical transaction of the transaction combination, and periodic characteristics of transaction power.

[0134] A privacy analysis module is configured to determine transaction privacy degree of the transaction combination based on encryption of the transaction combination to transaction content during a transaction process, and determine a request threshold demand index of the transaction combination based on the protection attention factor and the transaction privacy degree.

[0135] An adaptive adjustment module is configured to adjust a preset rated QPS threshold based on the request threshold demand index to obtain an adaptive QPS threshold of the transaction combination, and perform a security protection measure on a transaction request of the power transaction platform based on the adaptive QPS threshold of each transaction combination.

[0136] Optionally, the transmission medium can be a wired link such as, but not limited to, a coaxial cable, an optical fiber, a digital subscriber line, and the like, or a wireless link such as, but not limited to, a wireless fidelity (WIFI), a Bluetooth, a mobile device network, and the like.

[0137] It should be noted that the apparatus provided in the above embodiments is only used as an example for division of the above functional modules, and in actual applications, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the above described functions.

[0138] Figure 5 is a structural schematic diagram of a computer device provided by an embodiment of the present application. As shown in the example of Figure 5 The computer device 500 includes a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and running on the processor 520, wherein the processor 520 executes the computer program 530, so that the computer device can execute any of the above-mentioned privacy information security protection methods for a power transaction platform.

[0139] In addition, an embodiment of the present application also protects an apparatus, which can include a memory and a processor, wherein the memory stores executable program code, and the processor is configured to invoke and execute the executable program code to execute the privacy information security protection method for a power transaction platform provided by an embodiment of the present application.

[0140] The embodiment of the present application can divide the functions of the device according to the above method examples, for example, each function module can be divided, two or more functions can be integrated in one processing module, and the integrated module can be realized in the form of hardware. It should be noted that the division of the modules in the embodiment is illustrative, and is only a logical function division. In actual implementation, another division mode can be used.

[0141] In the case of dividing each module according to each function, the device can further include a signal uploading module, a determination module, an adjustment module, and the like. It should be noted that all related contents of each step involved in the above method embodiment can be cited to the function description of the corresponding function module, and will not be described here.

[0142] It should be understood that the device provided by the embodiment of the present application is used to execute the above-mentioned method for protecting the privacy information of the power transaction platform, and thus the same effect as the above-mentioned implementation method can be achieved.

[0143] In the case of using an integrated unit, the device can include a processing module and a storage module. When the device is applied to a device, the processing module can be used to control and manage the actions of the device. The storage module can be used to support the device to execute mutual program codes and the like. The processing module can be a processor or a controller, which can realize or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure of the present application. The processor can also be a combination of computing functions, such as one or more microprocessor combinations, a combination of digital signal processing (Digital Signal Processing, DSP) and microprocessor, and the like. The storage module can be a memory.

[0144] In addition, the device provided by the embodiment of the present application can be a chip, an assembly or a module. The chip can include a connected processor and a memory. The memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the method for protecting the privacy information of the power transaction platform provided by the above-mentioned embodiment.

[0145] The embodiment of the present application also provides a computer readable storage medium, which stores computer program codes. When the computer program codes run on a computer, the computer can execute the above-mentioned related method steps to realize the method for protecting the privacy information of the power transaction platform provided by the above-mentioned embodiment.

[0146] The embodiment of the present application also provides a computer program product. When the computer program product runs on a computer, the computer can execute the above-mentioned related steps to realize the method for protecting the privacy information of the power transaction platform provided by the above-mentioned embodiment.

[0147] Wherein, the device, computer readable storage medium, computer program product or chip provided by the embodiments of the present application are used to execute the corresponding method provided above, thus the beneficial effects achieved thereby can refer to the beneficial effects of the corresponding method provided above, which will not be repeated here. Through the description of the above embodiments, those skilled in the art can understand that, for the convenience and brevity of description, only the division of the above functional modules is taken as an example, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In the embodiments provided by the present application, it should be understood that the disclosed device and method can be implemented in other ways.

[0148] The device embodiments described above are only schematic, for example, the division of the modules or units is only a logical function division, and there can be another division in actual implementation, for example, a plurality of units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed mutual ones can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0149] It should also be noted that the terms "comprising", "including", or any other variant thereof, are intended to cover non-exclusive inclusion, so that processes, methods, articles or terminal devices including a series of elements not only include those elements, but also include other elements not explicitly listed, or further include elements inherent to such processes, methods, articles or terminal devices. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article or terminal device including the element.

[0150] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0151] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments.

[0152] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. 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the transaction combination during the transaction process are used to determine the transaction privacy degree of the transaction combination.

4. The method for privacy information security protection of electricity trading platform according to claim 1, characterized in that, The request threshold demand index of the transaction combination is determined by combining the protection-required importance factor and the transaction privacy degree, including: The ratio of the protection-required importance factor and the transaction privacy degree is taken as the request threshold demand index of the transaction combination.

5. The method for privacy information security protection of electricity trading platform according to claim 1, characterized in that, The adaptive QPS threshold of the transaction combination is obtained by adjusting the preset rated QPS threshold according to the request threshold demand index, including: The adjustment coefficient is determined by comparing the request threshold demand index and the standard request threshold demand index; The adaptive QPS threshold of the transaction combination is obtained by adjusting the preset rated QPS threshold with the adjustment coefficient as the weight.

6. A privacy information security protection system for a power trading platform, characterized in that, The system includes the following modules: An attack analysis module is configured to analyze real-time transaction demand and short-term transaction response delay of the power transaction platform, and determine an attack possibility of the power transaction platform suffering from a DDOS attack. The attack possibility of the power transaction platform suffering from the DDOS attack is determined according to a short-term change trend of IP access volume of the power transaction platform, a bandwidth degradation feature, and a remaining memory occupancy ratio, to determine a performance weakness presentation degree of the power transaction platform. The attack possibility of the power transaction platform suffering from the DDOS attack is determined by combining the performance weakness presentation degree and the short-term transaction response delay. The short-term change trend of the IP access volume of the power transaction platform is obtained by obtaining a ratio of the IP access volume of the power transaction platform at a current time to a maximum IP access volume as a first change trend, determining a second change trend according to a change of the IP access volume within a short-term reference time range corresponding to the current time, and combining the first change trend and the second change trend to obtain the short-term change trend. The first change trend and the second change trend are positively correlated with the short-term change trend. A protection analysis module is configured to determine a protection-required importance factor of a transaction combination by combining the attack possibility, historical transactions of the transaction combination, and periodic characteristics of transaction power. The protection-required importance factor of the transaction combination is determined by determining a power transaction confidence of the transaction combination according to the historical transactions of the transaction combination and the periodic characteristics of the transaction power, and combining the attack possibility and the power transaction confidence. The power transaction confidence of the transaction combination is determined by determining a time period characteristic value of the historical transactions of the transaction combination. The time period characteristic value represents a time interval error of the transaction. An electric quantity period characteristic value of the historical transactions of the transaction combination is determined. The electric quantity period characteristic value represents a transaction power error of the transaction. The power transaction confidence of the transaction combination is determined by combining the time period characteristic value and the electric quantity period characteristic value. The time period characteristic value and the electric quantity period characteristic value are negatively correlated with the power transaction confidence. The privacy analysis module is configured to determine a transaction privacy degree of the transaction combination according to an encryption condition when the transaction combination encrypts the transaction content during the transaction process; and determine a request threshold demand index of the transaction combination in combination with the attention factor to be protected and the transaction privacy degree. The adaptive adjustment module is configured to adjust a preset rated QPS threshold according to the request threshold demand index to obtain an adaptive QPS threshold of the transaction combination; and perform a security protection measure on the transaction request of the power transaction platform according to the adaptive QPS threshold of each transaction combination.

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