Network elasticity analysis method and device based on dynamic fault tree

Abstract

The invention discloses a network elasticity analysis method and device based on a dynamic fault tree, and belongs to the technical field of network security. The method comprises the following steps: taking an elastic target of a network system as a top event, and constructing a network elastic dynamic fault tree for the top event; obtaining historical operation and maintenance data of the network system, and calculating the occurrence probability of each basic event according to the historical operation and maintenance data; calculating the probability of occurrence of top events and the key importance of each basic event based on the probability of occurrence of the basic events and the logic relationship in the dynamic fault tree; and when the occurrence probability of the top event exceeds a preset threshold value, based on the key importance degree of each basic event and the occurrence probability of each basic event, analyzing to obtain a weak point of the network system, and generating a targeted network elasticity maintenance strategy to ensure the effectiveness of network elasticity. The method not only has high evaluation efficiency, but also can realize the maintenance of the network elasticity in the actual operation process of the network system.

Description

Technical Field

[0001] The present invention relates to the field of network security technology, and in particular to a network resilience analysis method and device based on a dynamic fault tree. Background Art

[0002] Network resilience refers to the ability of the network to prevent, withstand, recover and adapt when faced with adverse conditions, pressure, attacks or compromised components, in order to maintain the stability of system functions and structures, achieve an orderly and effective response to major network security incidents, and ensure the stable operation of key businesses.

[0003] In the related art, the network resilience analysis method for network systems is to use network simulation to construct network systems and attack behaviors, so as to evaluate the network resilience of network systems. However, this method is not only inefficient in evaluation, but also unable to achieve abnormal detection and maintenance of network resilience during the operation of actual network systems. Summary of the invention

[0004] The present invention provides a network resilience analysis method and device based on a dynamic fault tree. The technical solution is as follows: On the one hand, an embodiment of the present invention provides a network resilience analysis method based on a dynamic fault tree, the method comprising: The resilience target of the network system is taken as a top event to construct a network resilience dynamic fault tree for the top event; the dynamic fault tree includes top events, intermediate events and basic events, and the logical relationship between events at different levels includes at least one or more of a timing dependency gate, a cold spare gate and a basic logic gate; Obtaining historical operation and maintenance data of the network system, and calculating the probability of occurrence of each basic event based on the historical operation and maintenance data; Based on the occurrence probability of basic events and the logical relationship in the dynamic fault tree, the occurrence probability of the top event and the critical importance of each basic event are calculated; When the probability of occurrence of the top event exceeds the preset threshold, the weaknesses of the network system are analyzed based on the critical importance of each basic event and the probability of occurrence of each basic event, and a targeted network resilience maintenance strategy is generated to ensure the effectiveness of network resilience.

[0005] In a possible implementation, the historical operation and maintenance data includes at least one of: equipment parameters, historical fault records, attack logs, and current operation data of the network system; The probability of occurrence of each basic event is calculated based on the historical operation and maintenance data, including: For each basic event, the following steps are performed: based on an occurrence threshold set in advance for the basic event, the proportion of the historical operation and maintenance data that meets the occurrence threshold is counted, and the occurrence probability of the basic event is determined based on the proportion.

[0006] In a possible implementation, determining the probability of occurrence of the basic event based on the proportion includes: According to the logical relationship in the dynamic fault tree, determine whether the basic event depends on the occurrence of other basic events; if so, the probability of occurrence of the basic event is calculated using conditional probability according to the proportion of the basic event and the probability of occurrence of other basic events on which it depends.

[0007] In a possible implementation, when the network system detects that the system function corresponding to the elastic target fails, it is used to start the system recovery process, and the system recovery process is started in the following manner: first start the main system recovery process, and if the main system recovery fails, start the redundant system recovery process; The dynamic fault tree includes at least two intermediate events, namely, failure of primary system recovery and failure of redundant system recovery, and the two intermediate events are expressed in a logical relationship with the top event through a cold spare gate.

[0008] In a possible implementation, if the basic events of the main system recovery failure include the detection delay and the main system data recovery with dependent timing, and the basic events of the redundant system recovery failure include the redundant system startup failure and the redundant system data synchronization failure with an OR relationship, then: The probability of the redundant system recovery failure is calculated by the following conditional probability formula: P(Redundant system recovery failure | Primary system recovery failure) = P(BE 3 )+P(BE 4 )-P(BE 3 ∩BE 4 ) Where P(redundant system recovery failure | main system recovery failure) is the probability of redundant system recovery failure, P(BE 3 ) is the probability of redundant system startup failure, P(BE 4 ) is the probability of redundant system data synchronization failure; The probability of failure of the main system recovery is calculated by the following formula: P(main system recovery failure) = P(BE 1 )P(BE 2 ) Among them, P(main system recovery failure) is the probability of failure of main system recovery, P(BE 1 ) is the probability of occurrence of detection delay, P(BE 2) is the probability of failure in data recovery of the main system; The probability of occurrence of the top event is calculated by the following formula: P(Top)=P(main system recovery failure)×P(redundant system recovery failure|main system recovery failure) Among them, P(Top) is the probability of occurrence of the top event, and P(main system recovery failure) is the probability of occurrence of main system recovery failure.

[0009] In one possible implementation, the critical importance of each basic event is calculated as follows: For each basic event, execute: Calculate the probability importance of the basic event; the probability importance is used to characterize the influence of the change in the probability of occurrence of the basic event on the probability of occurrence of the top event; Calculate the probability of occurrence of the basic event divided by the probability of occurrence of the top event, and multiply the calculated quotient by the probability importance of the basic event, and use the product as the key importance of the basic event.

[0010] On the other hand, an embodiment of the present invention provides a network resilience analysis device based on a dynamic fault tree, the device comprising: A construction unit is used to take the resilience target of the network system as a top event to construct a network resilience dynamic fault tree for the top event; the dynamic fault tree includes top events, intermediate events and basic events, and the logical relationship between events at different levels includes at least one or more of a timing dependency gate, a cold spare gate and a basic logic gate; An acquisition unit, used to acquire historical operation and maintenance data of the network system; A calculation unit, used to calculate the occurrence probability of each basic event according to the historical operation and maintenance data; and to calculate the occurrence probability of the top event and the critical importance of each basic event based on the occurrence probability of the basic event and the logical relationship in the dynamic fault tree; The analysis unit is used to analyze the weaknesses of the network system based on the critical importance of each basic event and the probability of occurrence of each basic event when the probability of occurrence of the top event exceeds a preset threshold, and generate a targeted network resilience maintenance strategy to ensure the effectiveness of network resilience.

[0011] On the other hand, a computer device is provided, which includes a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of the above-mentioned network resilience analysis method based on dynamic fault tree.

[0012] On the other hand, a computer-readable storage medium is provided, wherein a computer program is stored in the storage medium, and when the computer program is executed by a processor, the steps of the network resilience analysis method based on the dynamic fault tree are implemented.

[0013] On the other hand, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the above-mentioned network resilience analysis method based on a dynamic fault tree are implemented.

[0014] The technical solution provided by the present invention can at least bring the following beneficial effects: By taking the resilience target of the network system as the top event, a network resilience dynamic fault tree is constructed for the top event. The historical operation and maintenance data obtained during the operation of the network system is used to calculate the probability of occurrence of each basic event. Then, the probability of occurrence of the top event and the critical importance of the basic event are calculated using the probability of occurrence of the basic event and the logical relationship of the dynamic fault tree, so as to analyze the weak points of network resilience. Finally, targeted maintenance strategies are generated for the weak points to ensure the effectiveness of network resilience. It can be seen that this scheme can realize the rapid evaluation of network resilience during the operation of the network system, and can quantitatively analyze and calculate the resilience failure behavior of the network system with timing dependence and cold spare logic, and there is no need for network simulation. It not only has high evaluation efficiency, but also can realize the maintenance of network resilience during the operation of the actual network system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] 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 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.

[0016] Figure 1 It is a flow chart of a network resilience analysis method based on a dynamic fault tree provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of a network resilience dynamic fault tree of a network system provided by an embodiment of the present invention; Figure 3 It is a structural diagram of a network resilience analysis device based on a dynamic fault tree provided by an embodiment of the present invention; Figure 4 It is a hardware architecture diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0018] Please refer to Figure 1 , an embodiment of the present invention provides a network resilience analysis method based on a dynamic fault tree, the method comprising: Step 100, taking the resilience target of the network system as a top event, and constructing a network resilience dynamic fault tree for the top event; the dynamic fault tree includes top events, intermediate events, and basic events, and the logical relationship between events at different levels includes at least one or more of a timing dependency gate, a cold spare gate, and a basic logic gate; Step 102: Obtain historical operation and maintenance data of the network system, and calculate the occurrence probability of each basic event based on the historical operation and maintenance data; Step 104: Based on the occurrence probability of basic events and the logical relationship in the dynamic fault tree, the occurrence probability of the top event and the critical importance of each basic event are calculated; Step 106, based on the occurrence probability of the top event and the critical importance of each basic event, analyze the weaknesses of the network system and generate a targeted network resilience maintenance strategy to ensure the effectiveness of network resilience.

[0019] In the embodiment of the present invention, the elasticity target of the network system is taken as the top event to construct a network elasticity dynamic fault tree for the top event, and the historical operation and maintenance data obtained during the operation of the network system is used to calculate the probability of occurrence of each basic event. Then, the probability of occurrence of the top event and the critical importance of the basic event are calculated using the probability of occurrence of the basic event and the logical relationship of the dynamic fault tree, so as to analyze the weak points of network elasticity. Finally, a targeted maintenance strategy is generated for the weak points to ensure the effectiveness of network elasticity. It can be seen that this solution can realize the rapid evaluation of network elasticity during the operation of the network system, can quantitatively analyze and calculate the elastic failure behavior of the network system with timing dependence and cold spare logic, and does not need to perform network simulation. It not only has a high evaluation efficiency, but also can realize the maintenance of network elasticity during the operation of the actual network system.

[0020] Described below Figure 1 How the various steps are performed.

[0021] First, for step 100, the resilience target of the network system is taken as a top event to construct a network resilience dynamic fault tree for the top event.

[0022] In the embodiment of the present invention, for a network system, the resilience targets it is concerned about may include multiple ones. Since different resilience targets are associated with different events, the resilience target can be used as a top event to construct a corresponding network resilience dynamic fault tree for the top event.

[0023] A fault tree is an inverted tree-like logical causal relationship diagram that uses event symbols, logic gate symbols, and transfer symbols to describe the causal relationship between various events in the system; among them, the input event of the logic gate is the "cause" of the output event, and the output event of the logic gate is the "effect" of the input event.

[0024] In an embodiment of the present invention, when constructing a network resilience dynamic fault tree for a top event, it can specifically include: determining the intermediate events in the network system that affect the network resilience of the top event, and determining the logical relationship between the intermediate events and the top event, and determining the basic events that cause the failure of the network resilience of the top event based on the logical relationship; generating a network resilience fault tree according to the top event, the intermediate events, the basic events and the logical relationship. Among them, the logical relationship between events at different levels includes at least one or more of a timing dependency gate (PAND), a cold spare part gate (CSP) and a basic logic gate (AND / OR). Among them, the intermediate events and the basic events are determined using different functional structure levels associated with the top event.

[0025] The method provided by the embodiment of the present invention can be applied to at least the following scenarios: when the network system detects that the system function corresponding to the elastic target fails, it is used to start the system recovery process, and the system recovery process is started in the following manner: first start the main system recovery process, and if the main system recovery fails, start the redundant system recovery process; Then, the constructed dynamic fault tree includes at least two intermediate events: failure of primary system recovery and failure of redundant system recovery, and the two intermediate events are expressed in logical relationship with the top event through the cold spare gate. Figure 2 , which is a schematic diagram of the dynamic fault tree constructed in this scenario. Among them, network service a1 is located in the key asset A of the network system. The interruption of network service a1 in the key asset A (i.e., network resilience failure) is taken as the top event, and a network resilience dynamic fault tree can be generated for this top event. Figure 2It can be seen that the intermediate events that affect the network resilience of the top event include the failure of the main system to recover and the failure of the redundant system to recover; the basic events of the failure of the main system to recover include detection delay and failure of the main system data recovery; the basic events of the failure of the redundant system to recover include the failure of the redundant system to start and the failure of the redundant system data recovery. The redundant system and the main system are in a cold spare relationship. When the main system fails to recover, the redundant system is activated to take over the key business.

[0026] Figure 2 In the example, the dynamic fault tree uses PAND gates, OR gates, and CSP gates to associate the events.

[0027] In one embodiment, the definition and logical relationship of each event in the dynamic fault tree are configured as follows: Top event definition: Network service a1 interruption (response time > 10 minutes).

[0028] Among them, the occurrence of top events can be caused by network attacks or system failures.

[0029] Dynamic logic gate configuration: PAND gate (timing dependent gate) Input Event 1: Detection Delay (This event uses BE 1 to indicate that the detection time is >5 minutes); Input event 2: Primary system data recovery failed (this event uses BE 2 to indicate that the recovery time is > 5 minutes); Logical relationship: BE 1 Must be in BE 2 Happened before.

[0030] CSP Door (Cold Spare Door) Main event: Main system recovery failed (BE 2 =1); Backup event: Redundant system recovery failure, that is, redundant system startup failure (this event uses BE 3 to indicate) or redundant system data synchronization failure (this event uses BE 4 to indicate); Logical relationship: The redundant system recovery process is activated after the primary system recovery fails.

[0031] Then, for step 102, historical operation and maintenance data of the network system is obtained, and the occurrence probability of each basic event is calculated based on the historical operation and maintenance data.

[0032] In one embodiment of the present invention, the historical operation and maintenance data may include at least one of: device parameters, historical fault records, attack logs, and current operation data of the network system. The historical operation and maintenance data is data actually generated by the network system and can truly reflect the network elasticity of the network system.

[0033] It should be noted that the network elasticity analysis method in the embodiment of the present invention can be performed on a network system that is in operation. During the analysis process, it is only necessary to obtain the historical operation and maintenance data of the network system. There is no need to suspend the operation of the network system, and the normal operation of the network system will not be hindered.

[0034] In one embodiment of the present invention, the occurrence probability of each basic event is calculated in the following manner: for each basic event, the following is performed: based on the occurrence threshold set in advance for the basic event, the proportion of the historical operation and maintenance data that meets the occurrence threshold is counted, and the occurrence probability of the basic event is determined based on the proportion.

[0035] Among them, the proportion can be obtained by using statistical methods. Figure 2 Taking the basic event of detection delay as an example, according to the above definition, its occurrence threshold is 5 minutes. The total number of detection events in the historical operation and maintenance data and the total number of detection events with a detection time of more than 5 minutes are counted. The total number of detection events with a detection time of more than 5 minutes is divided by the total number of detection events to determine the proportion that meets the occurrence threshold.

[0036] If the basic event is an independent event, then after obtaining the percentage of the basic event, the percentage can be directly determined as the probability of occurrence of the basic event; If a basic event is not an independent event but is related to the occurrence of other basic events, then the percentage obtained from the statistics of the basic event cannot be used to determine the probability of occurrence of the basic event.

[0037] Based on this, in the embodiment of the present invention, determining the probability of occurrence of the basic event based on the proportion may include: According to the logical relationship in the dynamic fault tree, determine whether the basic event depends on the occurrence of other basic events; if so, the probability of occurrence of the basic event is calculated using conditional probability according to the proportion of the basic event and the probability of occurrence of other basic events on which it depends.

[0038] The following is for Figure 2 Calculate the probability of occurrence of each basic event.

[0039] Detection delay (BE 1): Count the percentage of attack events in which the detection time exceeds the occurrence threshold (5 minutes). For example, based on historical log statistics, if 10 out of 100 attacks have a detection delay exceeding the occurrence threshold, then the probability of occurrence of this basic event is: P(BE 1 )=0.10; Main system data recovery failed (BE 2 ): Due to the basic event BE 2 Occurrence and detection delay BE 1 It has time dependency, so it is necessary to use conditional probability for calculation; for example, according to historical attack log statistics, in the detection delay (BE 1 ) occurs, the failure rate of the main system recovery is 25% (10 main system recovery failures in 40 delay attacks), that is, the probability of occurrence of this basic event is: P(BE 2 ∣BE 1 )=0.25; Redundant system startup failure (BE 3 ): Count the number of times the redundant system fails to start after the main system fails to recover. For example, if 2 out of 10 master-slave switchings fail, the probability of this basic event is: P(BE 3 )=0.20; Redundant system data synchronization failed (BE 4 ): Count the number of data synchronization failures between the primary system and the redundant system. For example, if 5 out of 20 data synchronizations fail, the probability of this basic event is: P(BE 4 )=0.25.

[0040] Step 104, based on the occurrence probability of basic events and the logical relationship in the dynamic fault tree, the occurrence probability of the top event and the critical importance of each basic event are calculated.

[0041] In the embodiment of the present invention, in order to analyze whether the network elasticity of the elasticity target is effective, the occurrence probability of the top event can be used for analysis. After calculating the occurrence probability of the basic event, in order to calculate the occurrence probability of the top event, it is necessary to first calculate the occurrence probability of each intermediate event; Continue with Figure 2 Take the two intermediate events in the dynamic fault tree shown as an example.

[0042] For the intermediate event of failure of primary system recovery, the probability of occurrence is two basic events (BE 1 and BE 2 ), that is, P(main system recovery failure) = P(BE 1 )P(BE 2 )=0.1×0.25=0.025.

[0043] Among them, P(main system recovery failure) is the probability of failure of main system recovery, P(BE 1 ) is the probability of occurrence of detection delay, P(BE 2 ) is the probability of failure in data recovery of the primary system.

[0044] For the intermediate event of redundant system recovery failure, the primary system recovery failure (BE 2 =1), the redundant system recovery process is activated, and the probability of redundant system recovery failure is determined by the following basic events: redundant system startup failure (BE 3 ) and redundant system data synchronization failure (BE 4 ).

[0045] Then, the probability of redundant system recovery failure is calculated by the following conditional probability formula: P(Redundant system recovery failure | Primary system recovery failure) = P(BE 3 )+P(BE 4 )-P(BE 3 ∩BE 4 ) Where P(redundant system recovery failure | main system recovery failure) is the probability of redundant system recovery failure, P(BE 3 ) is the probability of redundant system startup failure, P(BE 4 ) is the probability of redundant system data synchronization failure.

[0046] Assumption BE 3 (Redundant system startup failure) and BE 4 (Redundant system data synchronization failure) is an independent event, that is, there is no direct dependency between the two, then: P(Redundant system recovery failure | Primary system recovery failure) = P(BE 3 )+P(BE 4 )-P(BE 3 )P(BE 4 )=0.20+0.25-0.20×0.25=0.40.

[0047] In the embodiment of the present invention, after calculating the occurrence probabilities of the two intermediate events, it is considered that the failure of the main system recovery and the failure of the redundant system recovery are cold spare logic. The core of the cold spare logic is that the spare will be activated only after the main part fails. However, the success of the standby event does not directly depend on the state of the main event, but depends on the running state and resource availability of the standby event itself. That is: Main event: Main system recovery failed (BE 2 =1); Backup event: Redundant system recovery failure, that is, redundant system startup failure (BE 3 ) or redundant system data synchronization failure (BE 4 ); Logical relationship: After the main system fails to recover, the redundant system recovery process is activated. The probability of redundant system recovery failure is determined by BE 3 and BE 4 The joint probability P(redundant system recovery failure | primary system recovery failure) determines the

[0048] The condition for the top event (service interruption) to occur is that the primary system fails to recover and the redundant system fails to recover. Both must occur at the same time.

[0049] Then, the probability of the top event can be calculated by the following formula: P(Top)=P(main system recovery failure)×P(redundant system recovery failure|main system recovery failure)=0.025×0.40=0.01(i.e. 1%) Among them, P(Top) is the probability of occurrence of the top event.

[0050] After the occurrence probability of the top event is calculated, the critical importance of each basic event can be calculated using the occurrence probability of the top event.

[0051] In one implementation, the critical importance of each basic event is calculated as follows: Calculate the probability importance of the basic event; the probability importance is used to characterize the influence of the change in the probability of occurrence of the basic event on the probability of occurrence of the top event; Calculate the probability of occurrence of the basic event divided by the probability of occurrence of the top event, and multiply the calculated quotient by the probability importance of the basic event, and use the product as the key importance of the basic event.

[0052] Among them, the probability importance of the i-th basic event is calculated by the following formula: Calculate the probability importance I of each basic event p (BE i ), that is, the i-th basic event BE i The impact of the probability change on the probability of the top event. The calculation formula is: Among them, I p (BE i ) is the probability importance of the ith basic event, P(BE i ) is the probability of occurrence of the ith basic event.

[0053] Continue with Figure 2Take the dynamic fault tree shown in the figure as an example to calculate the critical importance of each basic event. Among them, for the cold spare design scenario, the calculation of probability importance needs to consider the conditional probability. Then: For the basic event BE of detection delay 1 , its probability importance is: =P(BE 2 |BE 1 )×P(Redundant system recovery failure | Primary system recovery failure) =0.25×0.40=0.10 For the basic event BE of failure of primary system data recovery 2 , its probability importance is: =P(BE 1 )×P(Redundant system recovery failure | Primary system recovery failure) =0.10×0.40=0.04 For the basic event BE of redundant system startup failure 3 , its probability importance is: =P(main system recovery failure)×(1-P(BE 4 )) =0.025×0.75=0.01875 For the basic event BE of redundant system data synchronization failure 4 , its probability importance is: =P(main system recovery failure)×(1-P(BE 3 )) =0.025×0.80=0.02 Then, based on the probability importance, the key importance, that is, the basic event BE, is calculated. i The degree of influence of the change in the probability of occurrence of the top event on the probability of occurrence of the top event, which represents the contribution of the basic event to the probability of occurrence of the top event and is the basis for the priority sorting of the basic events.

[0054] In the embodiment of the present invention, the critical importance of the ith basic event is calculated using the following calculation formula: in, is the critical importance of the ith basic event.

[0055] Then for Figure 2Each basic event shown has the following key importance: For the basic event BE of detection delay 1 , its key importance for: For the basic event BE of failure of primary system data recovery 2 : First calculate the conditional probability: P(BE 2 ∣BE 1 )=0.25P(BE 2 ∣BE 1 )=0.25 Then the unconditional probability is: P(BE 2 )=P(BE 1 )×P(BE 2 ∣BE 1 )=0.10×0.25=0.025 Key Importance for: For the basic event BE of redundant system startup failure 3 , its key importance for: For the basic event BE of redundant system data synchronization failure 4 , its key importance for: In this way, the critical importance of each basic event is obtained.

[0056] Step 106, when the probability of occurrence of the top event exceeds a preset threshold, based on the critical importance of each basic event and the probability of occurrence of each basic event, the weaknesses of the network system are analyzed and a targeted network resilience maintenance strategy is generated to ensure the effectiveness of network resilience.

[0057] In the embodiment of the present invention, during the operation of the network system, the probability of occurrence of the top event of the network system can be calculated using the dynamic fault tree and the historical operation and maintenance data. That is to say, if the probability of occurrence of the top event determined based on the current historical operation and maintenance data is greater, it indicates that the network elasticity of the network system is worse and the network elasticity is more likely to fail. Therefore, a threshold can be set in advance, and the probability of occurrence of the top event is compared with the preset threshold to determine the vulnerability of the network elasticity. For example, assuming that the preset threshold is 0.008, since the calculated probability of occurrence of the top event is 0.01>0.008, attention should be paid to the risk of failure of the elasticity of the network system, and the weak points of network elasticity should be further analyzed.

[0058] Specifically, it is necessary to use the critical importance of each basic event and the occurrence probability of each basic event to analyze the weaknesses of the network system.

[0059] First, sort the key importance of each basic event from large to small. Figure 2 Taking the key importance of each basic event as an example, we can see that I c (BE 1 )=1.0、I c (BE 2 )=0.10、I c (BE 3 )=0.375、I c (BE 4 )=0.50, then the order of the key importance of basic events from large to small is: I c (BE 1 )>I c (BE 4 )>I c (BE 3 )>I c (BE 2 ) It can be seen that in the embodiments of the present invention: Detection delay (BE 1 ) is the primary weak point and needs to be optimized first; The second is the failure of redundant system data synchronization (BE 4 ) and redundant system startup failure (BE 3 ); Main system data recovery failed (BE 2 ) has the lowest critical importance and therefore has the lowest optimization priority.

[0060] Then, after sorting by critical importance, whether the basic events with the greatest critical importance need maintenance can be evaluated in combination with their probability of occurrence.

[0061] Specifically, a same maintenance threshold may be set for basic events, or corresponding maintenance thresholds may be set for different basic events. If the occurrence probability of a basic event exceeds its maintenance threshold, maintenance of the basic event is required.

[0062] The maintenance strategy is generated to reduce the probability of occurrence of basic events, and different basic events use different maintenance strategies. The maintenance strategy includes but is not limited to: prioritizing resource allocation, increasing maintenance frequency, and adding spare components.

[0063] It should be noted that if the generation of maintenance strategies for some basic events can reduce the occurrence probability of the top event to below a preset threshold, it is not necessary to generate maintenance strategies for all basic events.

[0064] Specifically, S1, determining a first basic event with the greatest critical importance among a plurality of basic events whose occurrence probability exceeds a maintenance threshold, and generating a corresponding maintenance strategy for the first basic event; S2. After generating the current maintenance strategy, determine whether the probability of occurrence of the top event can be reduced to below the preset threshold. If so, end the process. Otherwise, among several basic events whose probability of occurrence exceeds the maintenance threshold and for which no maintenance strategy has been generated, determine the second basic event with the greatest critical importance, generate a corresponding maintenance strategy for the second basic event, and continue to execute S2.

[0065] The embodiment of the present invention analyzes the weak points of network elasticity and generates a maintenance strategy for reducing the probability of network elasticity failure and improving the overall network elasticity, thereby realizing the maintenance of network elasticity during the operation of an actual network system.

[0066] Please refer to Figure 3 The embodiment of the present invention provides a network resilience analysis device based on a dynamic fault tree, the device comprising: A construction unit 300 is used to take the resilience target of the network system as a top event to construct a network resilience dynamic fault tree for the top event; the dynamic fault tree includes a top event, an intermediate event, and a basic event, and the logical relationship between events at different levels includes at least one or more of a timing dependency gate, a cold spare gate, and a basic logic gate; An acquisition unit 302 is used to acquire historical operation and maintenance data of the network system; The calculation unit 304 is used to calculate the occurrence probability of each basic event according to the historical operation and maintenance data; and to calculate the occurrence probability of the top event and the critical importance of each basic event based on the occurrence probability of the basic event and the logical relationship in the dynamic fault tree; The analysis unit 306 is used to analyze the weaknesses of the network system based on the critical importance of each basic event and the probability of occurrence of each basic event when the probability of occurrence of the top event exceeds a preset threshold, and generate a targeted network resilience maintenance strategy to ensure the effectiveness of network resilience.

[0067] In one embodiment of the present invention, the historical operation and maintenance data includes: at least one of equipment parameters, historical fault records, attack logs, and current operation data of the network system; When the calculation unit calculates the occurrence probability of each basic event based on the historical operation and maintenance data, it specifically includes: for each basic event, it executes: based on the occurrence threshold set in advance for the basic event, counting the proportion of the historical operation and maintenance data that meets the occurrence threshold, and determining the occurrence probability of the basic event based on the proportion.

[0068] In one embodiment of the present invention, when the calculation unit executes the determination of the occurrence probability of the basic event based on the proportion, it specifically includes: determining whether the basic event depends on the occurrence of other basic events according to the logical relationship in the dynamic fault tree; if so, using conditional probability calculation to obtain the occurrence probability of the basic event according to the proportion of the basic event and the occurrence probability of other basic events on which it depends.

[0069] In one embodiment of the present invention, the network system is used to start a system recovery process when detecting that the system function corresponding to the elastic target fails, and the system recovery process is started in the following manner: first start the main system recovery process, and if the main system recovery fails, start the redundant system recovery process; The dynamic fault tree includes at least two intermediate events, namely, failure of primary system recovery and failure of redundant system recovery, and the two intermediate events are expressed in a logical relationship with the top event through a cold spare gate.

[0070] In one embodiment of the present invention, if the basic events of the main system recovery failure include the detection delay and the main system data recovery with dependent timing, and the basic events of the redundant system recovery failure include the redundant system startup failure and the redundant system data synchronization failure with an OR relationship, then: The probability of the redundant system recovery failure is calculated by the following conditional probability formula: P(Redundant system recovery failure | Primary system recovery failure) = P(BE 3 )+P(BE 4 )-P(BE 3 ∩BE 4 ) Where P(redundant system recovery failure | main system recovery failure) is the probability of redundant system recovery failure, P(BE3 ) is the probability of redundant system startup failure, P(BE 4 ) is the probability of redundant system data synchronization failure; The probability of failure of the main system recovery is calculated by the following formula: P(main system recovery failure) = P(BE 1 )P(BE 2 ) Among them, P(main system recovery failure) is the probability of failure of main system recovery, P(BE 1 ) is the probability of occurrence of detection delay, P(BE 2 ) is the probability of failure in data recovery of the main system; The probability of occurrence of the top event is calculated by the following formula: P(Top)=P(main system recovery failure)×P(redundant system recovery failure|main system recovery failure) Among them, P(Top) is the probability of occurrence of the top event, and P(main system recovery failure) is the probability of occurrence of main system recovery failure.

[0071] In one embodiment of the present invention, the critical importance of each basic event is calculated as follows: For each basic event, the following steps are performed: calculating the probability importance of the basic event; the probability importance is used to characterize the degree of influence of the change in the occurrence probability of the basic event on the occurrence probability of the top event; calculating the occurrence probability of the basic event divided by the occurrence probability of the top event, and multiplying the calculated quotient by the probability importance of the basic event, and taking the product as the key importance of the basic event.

[0072] It should be noted that the network resilience analysis device based on dynamic fault tree provided in the above embodiment is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, 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 addition, the network resilience analysis device for the network system provided in the above embodiment and the network resilience analysis method embodiment of the network system belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0073] The embodiment of the present application also provides a computer device, please refer to Figure 4 The computer device includes a processor and a memory, in which at least one instruction, at least one program, code set or instruction set is stored, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor to implement the network resilience analysis method based on dynamic fault tree provided by the above-mentioned method embodiments.

[0074] An embodiment of the present application also provides a computer-readable storage medium, on which is stored at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement the network resilience analysis method based on the dynamic fault tree provided in the above-mentioned method embodiments.

[0075] An embodiment of the present application also provides a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the network resilience analysis method based on a dynamic fault tree as described in any of the above embodiments.

[0076] For the convenience of description, the above system or device is described by dividing it into various modules or units according to its functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0077] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly contributed to the prior art in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0078] Finally, it should be noted that, in this article, relational terms such as first, second, third and fourth are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0079] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A network resilience analysis method based on dynamic fault tree, characterized in that: The method comprises: The resilience target of the network system is taken as a top event to construct a network resilience dynamic fault tree for the top event; the dynamic fault tree includes top events, intermediate events and basic events, and the logical relationship between events at different levels includes at least one or more of a timing dependency gate, a cold spare gate and a basic logic gate; Obtaining historical operation and maintenance data of the network system, and calculating the probability of occurrence of each basic event based on the historical operation and maintenance data; Based on the occurrence probability of basic events and the logical relationship in the dynamic fault tree, the occurrence probability of the top event and the critical importance of each basic event are calculated; When the probability of occurrence of the top event exceeds the preset threshold, the weaknesses of the network system are analyzed based on the critical importance of each basic event and the probability of occurrence of each basic event, and a targeted network resilience maintenance strategy is generated to ensure the effectiveness of network resilience.

2. The method according to claim 1, characterized in that The historical operation and maintenance data includes: at least one of equipment parameters, historical fault records, attack logs, and current operation data of the network system; The probability of occurrence of each basic event is calculated based on the historical operation and maintenance data, including: For each basic event, the following steps are performed: based on an occurrence threshold set in advance for the basic event, the proportion of the historical operation and maintenance data that meets the occurrence threshold is counted, and the occurrence probability of the basic event is determined based on the proportion.

3. The method according to claim 2, characterized in that Determining the probability of occurrence of the basic event based on the proportion includes: According to the logical relationship in the dynamic fault tree, determine whether the basic event depends on the occurrence of other basic events; if so, the probability of occurrence of the basic event is calculated using conditional probability according to the proportion of the basic event and the probability of occurrence of other basic events on which it depends.

4. The method according to claim 1, characterized in that The network system is used to start the system recovery process when detecting that the system function corresponding to the elastic target fails, and the system recovery process is started in the following manner: first start the main system recovery process, and if the main system recovery fails, start the redundant system recovery process; The dynamic fault tree includes at least two intermediate events, namely, failure of primary system recovery and failure of redundant system recovery, and the two intermediate events are expressed in a logical relationship with the top event through a cold spare gate.

5. The method according to claim 4, characterized in that If the basic events of the primary system recovery failure include the detection delay and the primary system data recovery with dependent timing, and the basic events of the redundant system recovery failure include the redundant system startup failure and the redundant system data synchronization failure with an OR relationship, then: The probability of the redundant system recovery failure is calculated by the following conditional probability formula: P(Redundant system recovery failure | Primary system recovery failure) = P(BE3) + P(BE4) - P(BE3∩BE4) Wherein, P(redundant system recovery failure|main system recovery failure) is the probability of redundant system recovery failure, P(BE3) is the probability of redundant system startup failure, and P(BE4) is the probability of redundant system data synchronization failure. The probability of failure of the main system recovery is calculated by the following formula: P(main system recovery failure)=P(BE1)P(BE2) Among them, P(main system recovery failure) is the probability of failure of main system recovery, P(BE1) is the probability of detection delay, and P(BE2) is the probability of failure of main system data recovery; The probability of occurrence of the top event is calculated by the following formula: P(Top)=P(main system recovery failure)×P(redundant system recovery failure|main system recovery failure) Among them, P(Top) is the probability of occurrence of the top event, and P(main system recovery failure) is the probability of occurrence of main system recovery failure.

6. The method according to any one of claims 1 to 5, characterized in that: The critical importance of each basic event is calculated as follows: For each basic event, execute: Calculate the probability importance of the basic event; the probability importance is used to characterize the influence of the change in the probability of occurrence of the basic event on the probability of occurrence of the top event; Calculate the probability of occurrence of the basic event divided by the probability of occurrence of the top event, and multiply the calculated quotient by the probability importance of the basic event, and use the product as the key importance of the basic event.

7. A network resilience analysis device based on a dynamic fault tree, characterized in that: The device comprises: A construction unit is used to take the resilience target of the network system as a top event to construct a network resilience dynamic fault tree for the top event; the dynamic fault tree includes top events, intermediate events and basic events, and the logical relationship between events at different levels includes at least one or more of a timing dependency gate, a cold spare gate and a basic logic gate; An acquisition unit, used to acquire historical operation and maintenance data of the network system; A calculation unit, used to calculate the occurrence probability of each basic event according to the historical operation and maintenance data; and to calculate the occurrence probability of the top event and the critical importance of each basic event based on the occurrence probability of the basic event and the logical relationship in the dynamic fault tree; The analysis unit is used to analyze the weaknesses of the network system based on the critical importance of each basic event and the probability of occurrence of each basic event when the probability of occurrence of the top event exceeds a preset threshold, and generate a targeted network resilience maintenance strategy to ensure the effectiveness of network resilience.

8. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of any one of the methods described in claims 1-6.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The method comprises a computer program, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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