A coordinated optimization method and system for functional safety and information security of intelligent instruments

Abstract

The present invention discloses a coordinated optimization method and system for the functional safety and information security of smart meters. The method comprises: classifying the functional safety tasks and information security tasks of smart meters according to preset types, grouping them according to protection targets, and obtaining safety-related task groups; deleting information security tasks that conflict with functional safety tasks in each safety-related task group, and retaining only information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities to obtain an initial task set; each task includes attributes of risk mitigation capability, memory usage, and time cost; and selecting at least one task that meets preset conditions and has the greatest sum of risk mitigation capabilities from the initial task set to form a coordinated optimization task set. The method realizes the coordinated optimization of the functional safety tasks and information security tasks of smart meters, has a wide range of applications, and ensures the functional reliability, real-time performance, and low power consumption of smart meters.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent instrument safety protection, and more specifically, relates to a coordinated optimization method and system for intelligent instrument functional safety and information security. Background Art

[0002] Industrial control systems belong to production and operation systems, and their applications involve many safety-critical areas. It is crucial to ensure their safe operation.

[0003] While the application of embedded real-time operating systems and bus communication technologies in smart instruments improves their real-time performance, it also introduces more functional safety failure factors and information security threats. Therefore, there is an urgent need for functional safety and information security protection in smart instruments. Currently, implementation plans for functional safety tasks in smart instruments are relatively mature. However, due to their different functions and protection objectives, functional safety and information security tasks often contain redundancy and conflict. Without considering the coordinated optimization of these two tasks, running these tasks will impact the efficiency of smart instruments and, in severe cases, could severely compromise the smooth operation of industrial control systems.

[0004] Current functional safety and information security task coordination methods are mainly targeted at industrial control systems. Smart instruments often use dedicated operating systems with high real-time performance and relatively limited internal storage resources. Currently, there is no functional safety and information security task coordination optimization method suitable for smart instruments. Summary of the Invention

[0005] In response to the shortcomings of related technologies, the purpose of the present invention is to provide a method and system for coordinating and optimizing the functional safety and information security of smart meters, aiming to solve the problem that existing smart meter management methods cannot simultaneously meet the coordination problem of the real-time and security of smart meter tasks due to relatively limited internal storage resources.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a method for coordinated optimization of functional safety and information security of smart meters, comprising:

[0007] After classifying the functional safety tasks and information security tasks of smart instruments according to preset types, they are grouped according to protection targets to obtain safety-related task groups;

[0008] After deleting information security tasks that conflict with functional safety tasks in each of the safety-related task groups, only the information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities are retained to obtain an initial task set; each task includes risk mitigation capability, memory usage, and time cost attributes;

[0009] At least one task that meets preset conditions and has the largest sum of risk mitigation capabilities is selected from the initial task set to form a coordinated optimization task set.

[0010] Optionally, the preset condition is: the sum of memory occupancy is less than the preset memory occupancy, and the sum of time cost is less than the preset time cost.

[0011] Optionally, if there are multiple information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities, only one information security task and / or functional safety task with the greatest risk mitigation capability is retained.

[0012] Optionally, selecting at least one task that meets preset conditions and has the largest sum of risk mitigation capabilities from the initial task set to form a coordinated optimization task set includes:

[0013] Building a security task model based on attribute parameters of the execution cycle, execution time, risk mitigation capability, and memory usage of the tasks in the initial task set;

[0014] The security task model is as follows:

[0015] r j =(v j ,c j ,w j ,e j )

[0016] Among them, v j is the mission's risk mitigation capability, c j is the task cycle, w j is the execution time of the task, e j The memory usage of the task;

[0017] Constraining the safety task model through a risk mitigation capability optimization function, a time cost optimization function, and a memory usage optimization function;

[0018] The safety task model satisfies the following constraints:

[0019]

[0020] The decision variables are:

[0021] x={x1,…,x j ,…,x k}

[0022] Where k is the number of tasks in the initial task set, PT is the risk mitigation capability optimization function of the smart instrument functional safety and information security task set, ET is the time cost optimization function of the smart instrument functional safety and information security task set, EE represents the memory usage optimization function of the smart instrument functional safety and information security task set, and x j =1 means that the task is retained during the optimization process, x j =0 means the task is abandoned;

[0023] The NSGA-Ⅱ algorithm is used to solve the safety task model, and the solution with the optimal risk mitigation capability is obtained under the constraints of time cost and memory usage, which is used as the coordinated optimization task set for the functional safety and information security of smart instruments.

[0024] Optionally, after classifying the functional safety tasks and information security tasks of the smart meter according to preset types and grouping them according to protection targets to obtain safety-related task groups, the following steps are included:

[0025] Analyze the functional failure events that functional safety tasks and information security tasks respectively prevent;

[0026] Combined with the fuzzy matrix discrimination method, the severity of each functional failure event is graded; the characteristic roots of the fuzzy matrix are calculated, and the characteristic vector corresponding to the maximum characteristic root is set as P = (q1, q2, ...q n ), in q1,q2,…q n In the interval between the maximum and minimum values, the n values ​​are evenly divided into five equal parts and fuzzified to obtain the severity level δ of the functional failure event of the smart instrument m ,δ m ∈{1,2,3,4,5};

[0027] Among them, the constructed fuzzy matrix is ​​as follows:

[0028]

[0029] Among them, j xy ·j yx =1; x,y=1,2,…,n,j xy Indicates a functional failure event a x Relative to a y the severity of the consequences;

[0030] The safety task risk mitigation capability is calculated based on the severity level of the functional failure event. The quantitative formula for the safety task risk mitigation capability is as follows:

[0031]

[0032] Where n is the number of functional failure events that the smart instrument safety task can mitigate, v j is the risk mitigation capability attribute of the jth safety task, δ m Score the severity level of the consequences of functional failure of the mth smart instrument that mitigates the safety task.

[0033] Optionally, the preset types include defense type and response type.

[0034] In a second aspect, the present invention further provides a coordinated optimization system for functional safety and information security of smart meters, comprising:

[0035] The classification and grouping module is used to classify the functional safety tasks and information security tasks of smart instruments according to preset types, group them according to protection targets, and obtain safety-related task groups;

[0036] a screening module configured to remove information security tasks that conflict with functional safety tasks in each of the safety-related task groups and retain only information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities, thereby obtaining an initial task set; each task including attributes of risk mitigation capability, memory usage, and time cost;

[0037] The optimization module is used to select at least one task that meets preset conditions and has the largest sum of risk mitigation capabilities from the initial task set to form a coordinated optimization task set.

[0038] In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:

[0039] (1) The technical solution of the present invention simplifies the implementation steps of task conflict reduction and redundancy elimination by classifying tasks and grouping them according to protection objectives, improves the efficiency of task coordination, and realizes the coordinated optimization of smart instrument functional safety tasks and information security tasks from the perspective of task functional characteristics and protection objectives.

[0040] (2) The technical solution of the present invention combines the real-time, resource-limited, and low-power characteristics of smart meters. The proposed coordination optimization method uses a multi-objective optimization algorithm to optimize the task set after eliminating conflicts and redundancies, avoiding the subjectivity of human judgment and screening. The optimized coordination task set is more suitable for smart meters. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flowchart of a coordinated optimization method for functional safety and information security of a smart meter provided by an embodiment of the present invention;

[0042] Figure 2 A schematic diagram of the general functional module structure of a smart meter provided by an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of a process for resolving conflicts between functional safety tasks and information security tasks provided by an embodiment of the present invention;

[0044] Figure 4 A schematic diagram of a process for eliminating redundancy in functional safety tasks and information security tasks provided by an embodiment of the present invention;

[0045] Figure 5 A schematic diagram of a process flow for scoring the severity of consequences of functional failures provided by an embodiment of the present invention;

[0046] Figure 6 This is a flow chart of the NSGA-Ⅱ algorithm used in the embodiment. DETAILED DESCRIPTION

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0048] The contents involved in the above embodiment are described below in conjunction with a preferred embodiment.

[0049] Example 1

[0050] Figure 1 A flowchart of a method for coordinated optimization of functional safety and information security of a smart meter provided by an embodiment of the present invention.

[0051] like Figure 1-2 As shown in FIG, a coordinated optimization method for functional safety and information security of smart meters includes:

[0052] S1. After classifying the functional safety tasks and information security tasks of smart instruments according to preset types, group them according to protection targets to obtain safety-related task groups.

[0053] S2. After deleting the information security tasks that conflict with the functional safety tasks in each safety-related task group, only the information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities are retained to obtain an initial task set; each task includes risk mitigation capability, memory usage, and time cost attributes.

[0054] S3. Select at least one task that meets the preset conditions and has the largest sum of risk mitigation capabilities from the initial task set to form a coordinated optimization task set.

[0055] Functional safety and information security tasks of smart instruments are categorized based on their functional characteristics. These tasks are divided into two categories: defense tasks and response tasks. Defense tasks are tasks that prevent functional safety failures and information attacks from further penetrating the smart instrument. Response tasks are tasks that mitigate the consequences of functional failures caused by functional safety and information attacks. These categorized tasks are screened according to security task conflict resolution rules, and information security tasks that conflict with functional safety tasks within the same category are removed. These screened tasks are then screened again according to redundancy elimination rules, retaining the information security and / or functional safety tasks with the greatest risk mitigation capabilities while removing redundant tasks from the same task set. This results in an initial task set free of conflicts and redundancies. The objective attributes of functional safety and information security tasks include execution cycle, execution time, memory usage, and risk mitigation capabilities. By analyzing the objective attributes of the initial task set, a security task model is constructed. This security task model is then solved using a multi-objective optimization algorithm to obtain a coordinated and optimized task set for the functional safety and information security of smart instruments with the best risk mitigation capabilities. Therefore, the coordinated optimization of the functional safety tasks and information security tasks of smart instruments is achieved from the perspective of the functional characteristics and protection objectives of the tasks, ensuring the functional reliability, real-time performance and low power consumption of smart instruments.

[0056] Optionally, step S1 specifically includes:

[0057] S11. Classify functional safety tasks and information security tasks into defense and response categories.

[0058] S12. Analyze the protection targets of the classified defense tasks and response tasks respectively, group tasks with the same protection target into one group, and obtain a security-related task grouping set.

[0059] For example, the functional safety and information security tasks of smart meters are shown in Table 1.

[0060] Table 1 Example of functional safety and information security tasks for smart meters

[0061]

[0062] The protection objectives of smart instrument defense tasks and response tasks are analyzed, and tasks with the same or overlapping protection objectives are grouped together to obtain a set of security-related task groups.

[0063] Optionally, step S2 specifically includes:

[0064] S21. Select an information security task from each safety-related task group and determine whether there is a conflict with the functional safety tasks in other similar task groups in terms of protection objectives; if there is a conflict, delete the information security task; if not, retain it.

[0065] S22. Traverse the safety-related task grouping sets in sequence to obtain a conflict-free task set for functional safety and information security of the smart instrument.

[0066] S23. Select an information security task and / or functional safety task with the greatest risk mitigation capability from each safety-related task group in the non-conflicting task set, and delete the other information security tasks or functional safety tasks.

[0067] S24. Traverse each task group of the conflict-free task set in turn to obtain an initial task set.

[0068] like Figure 3 As shown, one information security task is selected from each task group in turn to determine whether there is a conflict in protection objectives with functional safety tasks in other similar task groups. If there is a conflict, the information security task is deleted. Because smart meters can be operated online, there are certain risks, and the most basic requirement of smart meters is to ensure real-time performance, so functional safety tasks have the highest priority. For example, the protection objective of the "role-based access control" defense task for smart meter information security is to ensure the integrity and confidentiality of smart meters, but this will affect the real-time protection objective of the functional safety strategy. Therefore, this task is deleted. If there are no information security tasks that conflict with the functional safety tasks, the tasks in the current task group are retained. Each security-related task group in the security-related task group set is traversed in turn to obtain a conflict-free task set for the functional safety and information security of smart meters.

[0069] like Figure 4 As shown in the figure, based on the conflict-free task set, one information security task or functional safety task with the greatest risk mitigation capability is selected from each safety-related task group in the conflict-free task set, and the corresponding redundant tasks are deleted. For example, referring to Table 1, for the smart instrument functional safety defense task "CRC check" and the information security defense task "MAC check," MAC check can detect functional safety failures such as packet loss in communication transmission even when a key is missing, and has high risk mitigation capability. Therefore, the CRC check task is deleted, while the MAC check task is retained. Since each safety-related task group represents the same protection objective, if there are multiple information security tasks or functional safety tasks in the same group, there is redundancy. The information security task or functional safety task with the greatest risk mitigation capability is selected, and the corresponding redundant tasks are deleted to eliminate redundancy. By traversing the conflict-free task set sequentially, the initial task set for the functional safety and information security of the smart instrument is obtained.

[0070] Furthermore, if there are multiple information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities, only one information security task and / or functional safety task with the greatest risk mitigation capability is retained.

[0071] For example, in a security-related task group of a conflict-free task set, there are multiple information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities, and the best one is selected from them based on other attributes, for example, a task with smaller memory usage or smaller time cost is selected.

[0072] For example, the tasks of integrating functional safety and information security of smart meters are shown in Table 2.

[0073] Table 2 Example of tasks for integrating functional safety and information security of smart instruments

[0074]

[0075] Because the target attributes of functional safety and information security tasks include multiple attributes such as execution cycle, execution time, memory usage, and risk mitigation capabilities, the risk mitigation capabilities of the functional safety and information security tasks of smart instruments must be determined before building the safety task model. The safety task model, including risk mitigation capabilities, is then constructed based on the execution cycle, execution time, and memory usage of the safety-related tasks.

[0076] The risk mitigation capability of the task needs to be obtained through calculation. Optionally, after obtaining the safety-related task grouping in step S1, the following steps are further included:

[0077] A1. Analyze the functional safety tasks and information security tasks corresponding to the functional failure events of protection.

[0078] A2. Combine the fuzzy matrix discrimination method to classify the severity of each functional failure event; calculate the characteristic root of the fuzzy matrix, and set the eigenvector corresponding to the largest characteristic root as P = (q1, q2, ...q n ), in q1,q2,…q n In the interval between the maximum and minimum values, the n values ​​are evenly divided into five equal parts and fuzzified to obtain the severity level δ of the functional failure event of the smart instrument m ,δ m ∈{1,2,3,4,5}.

[0079] Among them, the constructed fuzzy matrix is ​​as follows:

[0080]

[0081] Among them, j xy ·jyx =1; x,y=1,2,…,n,j xy Indicates a functional failure event a x Relative to a y The severity of the consequences.

[0082] A3. Calculate the safety task risk mitigation capability based on the severity level of the functional failure event. The quantitative formula for safety task risk mitigation capability is as follows:

[0083]

[0084] Where n is the number of functional failure events that the smart instrument safety task can mitigate, v j is the risk mitigation capability attribute of the jth safety task, δ m Score the severity level of the consequences of functional failure of the mth smart instrument that mitigates the safety task.

[0085] The consequences of functional failure events that can be mitigated by the functional safety tasks and information security tasks of smart meters are analyzed, as shown in Table 3.

[0086] Table 3 Analysis of smart meter function failure events

[0087]

[0088] Combined with the fuzzy matrix discrimination method, the severity of each functional failure event is graded. The functional failure consequence severity rating method is as follows: Figure 5 Step A2 specifically includes the following sub-steps:

[0089] A21. Determine and compare the consequences of intelligent instrument failure;

[0090] A22. Construct a fuzzy judgment matrix of the severity of the consequences of intelligent instrument function failure;

[0091] A23. Verify the consistency of the fuzzy judgment matrix of the severity of the consequences of intelligent instrument function failure;

[0092] A24 determines whether the consistency check passes. If so, execute A5. If not, return to execute A1.

[0093] A25. Find the eigenvector corresponding to the largest eigenroot of the fuzzy judgment matrix;

[0094] A26. Divide the interval consisting of the maximum and minimum values ​​of the eigenvector into equal parts and fuzzify them.

[0095] A27. Obtain the severity level of the consequences of smart instrument function failure.

[0096] The severity of each functional failure event is graded and a fuzzy matrix is ​​constructed to represent the severity of the consequences, as shown below:

[0097]

[0098] Among them, j xy ·j yx =1; x,y=1,2,…,n,j xy Indicates a functional failure event a x Relative to a y The severity of the consequences.

[0099] The severity judgment criteria for each functional failure event are shown in Table 4 below.

[0100] Table 4 Scaling table of elements in the judgment matrix

[0101] scale meaning 1 Indicates that two factors are equally important. 3 Indicates that one factor is slightly more important than the other factor. 5 Indicates that one factor is significantly more important than the other when comparing two factors. 7 Indicates that one factor is more important than the other. 9 Indicates that one factor is extremely more important than the other. 2，4，6，8 The median of the two adjacent judgments above 1 / 2,1 / 3,1 / 4,1 / 5,1 / 6,1 / 7,1 / 8,1 / 9 The diagonal symmetric positions of the matrix are in reciprocal relationship

[0102] After completing the judgment matrix J, its consistency is verified, and the verification index is:

[0103]

[0104] Among them, λ is the maximum eigenvalue of the judgment matrix J.

[0105] Obtain consistency ratio based on consistency index Wherein, RI is the average consistency index. The average consistency index values ​​in this embodiment are shown in Table 5:

[0106] Table 5 Average consistency index values

[0107] n 3 4 5 6 7 8 9 RI 0.52 0.89 1.12 1.24 1.32 1.41 1.45

[0108] When CR < 0.1, the consistency of J is considered to be within the allowable range and the consistency check passes. If CR ≥ 0.1, the consistency of J is considered to be no longer within the allowable range and the matrix value needs to be reselected until the consistency check passes.

[0109] Through the consistency check judgment matrix J, calculate its characteristic root, and set the characteristic vector P corresponding to the maximum characteristic root = (q1,q2,…q n ), in q1,q2,…q n In the interval between the maximum and minimum values, the n values ​​are evenly divided into five equal parts and fuzzified to obtain the severity level δ of the intelligent instrument function failure event. m ,δ m ∈{1,2,3,4,5}.

[0110] According to the risk mitigation capability quantification formula, the risk mitigation capability of the functional safety and information security tasks of smart instruments is determined. The quantification formula of the risk mitigation capability of security tasks is as follows:

[0111]

[0112] Where n is the number of functional failure events that the smart instrument safety task can mitigate, v j is the risk mitigation capability attribute of the jth safety task, δ m Score the severity level of the consequences of functional failure of the mth smart instrument that mitigates the safety task.

[0113] Optionally, step S3 can be divided into:

[0114] S31. Construct a security task model based on the attribute parameters of the execution cycle, execution time, risk mitigation capability and memory usage of the tasks in the initial task set.

[0115] S32. Constrain the safety task model through the risk mitigation capability optimization function, the time cost optimization function, and the memory usage optimization function.

[0116] S33. Combined with the NSGA-Ⅱ algorithm to solve the safety task model, the solution with the optimal risk mitigation capability under the premise of meeting the constraints of time cost and memory usage is obtained as the coordinated optimization task set for the functional safety and information security of smart instruments.

[0117] In step S31, the safety task model is as follows:

[0118] r j =(v j ,c j ,w j ,e j )

[0119] Among them, v j is the mission's risk mitigation capability, c j is the task cycle, w j is the execution time of the task, e j The memory usage of the task;

[0120] In step S32, the safety task model satisfies the following constraints:

[0121]

[0122] The decision variables are:

[0123] x={x1,…,x j ,…,x k}

[0124] Where k is the number of tasks in the initial task set, PT is the risk mitigation capability optimization function of the smart instrument functional safety and information security task set, ET is the time cost optimization function of the smart instrument functional safety and information security task set, EE represents the memory usage optimization function of the smart instrument functional safety and information security task set, and x j =1 means that the task is retained during the optimization process, x j =0 means the task is abandoned.

[0125] like Figure 6 As shown, step S33 specifically includes the following sub-steps:

[0126] S331. Randomly generate an initial population of size N. After non-dominated sorting, obtain the first-generation offspring population through the three basic operations of genetic algorithm: selection, crossover, and mutation. Secondly, starting from the second generation, merge the parent population and the offspring population, perform fast non-dominated sorting, and calculate the crowding degree of individuals in each non-dominated layer. Select appropriate individuals to form a new parent population based on the non-dominated relationship and the crowding degree of the individuals. Finally, generate a new offspring population through the basic operations of the genetic algorithm until the number of iterations reaches the set maximum number of iterations.

[0127] Among them, (a) select operation

[0128] Randomly select two individuals from N individuals, and according to the fitness value of each individual, select the individual with the best fitness value to enter the next generation population, and repeat this operation until N new individuals are obtained.

[0129] (b) Crossover operation

[0130] Two individuals are randomly selected from the parent population, and one of them is randomly selected to exchange gene fragments to obtain two new individuals, completing the crossover operation.

[0131] (c) Mutation operation

[0132] The mutation operation is achieved by flipping a bit in the parent individual gene. That is, if the selected bit is '0', this bit is flipped to '1'. If the selected bit is '1', this bit is flipped to '0'.

[0133] S332. Sort the Pareto task solution set obtained through iteration from high to low according to risk mitigation capability, and select the highest solution as the coordinated optimization task set for the functional safety and information security of the smart instrument.

[0134] The technical solution of the present invention classifies the functional safety tasks and information security tasks of smart meters, screens the classified tasks according to the rules of conflict resolution and redundancy elimination of security tasks, deletes the tasks with conflicts and redundancies in protection targets, obtains the initial task set, and then analyzes the target attributes of the functional safety tasks and information security tasks, constructs the security task model of the initial task set, and sets corresponding constraints. Under the conditions of meeting the preset memory occupancy and preset time cost, the solution is performed according to the multi-objective optimization algorithm to obtain the coordinated optimization task set with the best risk mitigation capability. The technical problem of the existing smart meter management method that the internal storage resources are relatively limited and cannot simultaneously meet the real-time and security requirements of the smart meter tasks is solved, and the coordinated optimization of the functional safety tasks and information security tasks of the smart meter is realized. The scope of application is wide, and the technical effects of functional reliability, real-time and low power consumption of the smart meter are guaranteed.

[0135] Example 2

[0136] A coordinated optimization system for functional safety and information security of smart instruments, including:

[0137] The classification and grouping module is used to classify the functional safety tasks and information security tasks of smart instruments according to preset types, group them according to protection targets, and obtain safety-related task groups;

[0138] a screening module configured to remove information security tasks that conflict with functional safety tasks in each of the safety-related task groups and retain only information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities, thereby obtaining an initial task set; each task including attributes of risk mitigation capability, memory usage, and time cost;

[0139] The optimization module is used to select at least one task that meets preset conditions and has the largest sum of risk mitigation capabilities from the initial task set to form a coordinated optimization task set.

[0140] The coordinated optimization system for the functional safety and information security of smart meters provided by an embodiment of the present invention can execute the coordinated optimization method for the functional safety and information security of smart meters provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0141] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A coordinated optimization method for functional safety and information security of smart meters, characterized in that: include: After classifying the functional safety tasks and information security tasks of smart instruments according to preset types, they are grouped according to protection targets to obtain safety-related task groups; After deleting information security tasks that conflict with functional safety tasks in each of the safety-related task groups, only the information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities are retained to obtain an initial task set; each task includes risk mitigation capability, memory usage, and time cost attributes; Building a security task model based on attribute parameters of the execution cycle, execution time, risk mitigation capability, and memory usage of the tasks in the initial task set; The security task model is as follows: r j =(v j ,c j ,w j ,e j ) Among them, v j is the mission's risk mitigation capability, c j is the task cycle, w j is the execution time of the task, e j The memory usage of the task; Constraining the safety task model through a risk mitigation capability optimization function, a time cost optimization function, and a memory usage optimization function; The safety task model satisfies the following constraints: The decision variables are: x={x1,…,x j ,…,x k } Where k is the number of tasks in the initial task set, PT is the risk mitigation capability optimization function of the smart instrument functional safety and information security task set, ET is the time cost optimization function of the smart instrument functional safety and information security task set, EE represents the memory usage optimization function of the smart instrument functional safety and information security task set, and x j =1 means that the task is retained during the optimization process, x j =0 means the task is abandoned; Solving the safety task model by using the NSGA-II algorithm, selecting at least one task that meets preset conditions and has the largest sum of risk mitigation capabilities from the initial task set as the coordinated optimization task set for the functional safety and information security of the smart instrument; The preset conditions are: the sum of memory occupancy is less than the preset memory occupancy, and the sum of time costs is less than the preset time cost.

2. The method according to claim 1, wherein If there are multiple information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities, only one information security task and / or functional safety task with the greatest risk mitigation capabilities shall be retained.

3. The method according to claim 1, wherein After the functional safety tasks and information security tasks of the smart instrument are classified according to the preset types and grouped according to the protection targets to obtain the safety-related task groups, the following are included: Analyze the functional failure events that functional safety tasks and information security tasks respectively prevent; Combined with the fuzzy matrix discrimination method, the severity of each functional failure event is graded; the characteristic roots of the fuzzy matrix are calculated, and the characteristic vector corresponding to the maximum characteristic root is set to P = (q1, q2, q n ), in q1,q2,q n In the interval between the maximum and minimum values, the n values ​​are evenly divided into five equal parts and fuzzified to obtain the severity level δ of the functional failure event of the smart instrument m ,δ m ∈{1,2,3,4,5}; Among them, the constructed fuzzy matrix is ​​as follows: Among them, j xy ·j yx =1; x,y=1,2,...,n,j xy Indicates a functional failure event a x Relative to a y the severity of the consequences; The safety task risk mitigation capability is calculated based on the severity level of the functional failure event. The quantitative formula for the safety task risk mitigation capability is as follows: Where n is the number of functional failure events that the smart instrument safety task can mitigate, v j is the risk mitigation capability attribute of the jth safety task, δ m Score the severity level of the consequences of functional failure of the mth smart instrument that mitigates the safety task.

4. The method according to claim 1, wherein The preset types include defense type and response type.

5. A coordinated optimization system for functional safety and information security of smart meters, characterized in that: include: The classification and grouping module is used to classify the functional safety tasks and information security tasks of smart instruments according to preset types, group them according to protection targets, and obtain safety-related task groups; a screening module configured to remove information security tasks that conflict with functional safety tasks in each of the safety-related task groups and retain only information security tasks and / or functional safety tasks with the greatest risk mitigation capabilities, thereby obtaining an initial task set; each task including attributes of risk mitigation capability, memory usage, and time cost; The optimization module performs the following steps: Building a security task model based on attribute parameters of the execution cycle, execution time, risk mitigation capability, and memory usage of the tasks in the initial task set; The security task model is as follows: r j =(v j ,c j ,w j ,e j ) Among them, v j is the mission's risk mitigation capability, c j is the task cycle, w j is the execution time of the task, e j The memory usage of the task; Constraining the safety task model through a risk mitigation capability optimization function, a time cost optimization function, and a memory usage optimization function; The safety task model satisfies the following constraints: The decision variables are: x={x1,…,x j ,…,x k } Where k is the number of tasks in the initial task set, PT is the risk mitigation capability optimization function of the smart instrument functional safety and information security task set, ET is the time cost optimization function of the smart instrument functional safety and information security task set, EE represents the memory usage optimization function of the smart instrument functional safety and information security task set, and x j =1 means that the task is retained during the optimization process, x j =0 means the task is abandoned; Solving the safety task model by using the NSGA-II algorithm, selecting at least one task that meets preset conditions and has the largest sum of risk mitigation capabilities from the initial task set as the coordinated optimization task set for the functional safety and information security of the smart instrument; The preset conditions are: the sum of memory occupancy is less than the preset memory occupancy, and the sum of time costs is less than the preset time cost.

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