WO2013114911A1 - Système d'évaluation de risque, procédé d'évaluation de risque, et programme - Google Patents

Système d'évaluation de risque, procédé d'évaluation de risque, et programme Download PDF

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Publication number
WO2013114911A1
WO2013114911A1 PCT/JP2013/050065 JP2013050065W WO2013114911A1 WO 2013114911 A1 WO2013114911 A1 WO 2013114911A1 JP 2013050065 W JP2013050065 W JP 2013050065W WO 2013114911 A1 WO2013114911 A1 WO 2013114911A1
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risk
storage unit
characteristic information
risk factor
information storage
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PCT/JP2013/050065
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English (en)
Japanese (ja)
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義晴 前野
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日本電気株式会社
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/008—Reliability or availability analysis

Definitions

  • the present invention relates to a risk evaluation system, a risk evaluation method, and a program.
  • an information processing system operated in a large-scale data center is often constructed by combining a large number of servers and routers.
  • an availability target value may be set. Therefore, when designing an information processing system, it is required to design such that availability reaches a target value.
  • MTBF Mean Time Between Failure
  • MTTR Mean Time To Repair
  • FIG. 8 shows an example of a probabilistic Petri net that defines the state transition of the virtual server.
  • the virtual server is also called a virtual machine (VM: Virtual Machine).
  • VM Virtual Machine
  • each state is represented by an oval box.
  • a “virtual server in operation” state indicating a normal operation state
  • a “virtual server stopped” state in which a user cannot use a service due to a failure
  • the virtual server here is not a hypervisor indicating a virtual machine control program that can be accessed only by a data center administrator, but is a general virtual machine that is assigned to a user and accessible by the user, that is, a user VM. That is.
  • Each transition is represented by a rectangular box indicating the event that causes the transition and the transition probability, and an arrow indicating the direction of the transition.
  • the transition from the “virtual server in operation” state to the “virtual server in operation” state occurs with a transition probability ⁇ if the physical server is in operation, and the transition probability 1 if the physical server is in operation. Occurs.
  • the transition from the “virtual server inactive” state to the “virtual server in operation” state occurs with a transition probability ⁇ if the physical server is in operation and the hypervisor is in operation. If the hypervisor is stopped, it occurs with a probability of zero.
  • a physical server is a physical computer on which a virtual server is executed.
  • the availability of the system can be analyzed. For example, the availability value can be calculated from the probability of transitioning to the “virtual server stopped” state after sufficient time has elapsed. Note that the state of “virtual server being stopped” is simply regarded as a failure, but in general, the availability value changes depending on the definition of the failure or operation. In general, each state and each transition described in the probabilistic Petri net is created one by one by taking into account the characteristics of the server infrastructure and the data center operation procedure related to the server infrastructure. Therefore, various availability prediction models may be created depending on the operation procedure.
  • Patent Document 1 the operating rate of the entire system is predicted based on characteristics such as the rate of occurrence of failures in individual computers constituting the system, the time taken to recover from failures, and monitoring information related to operating failures. A method is disclosed.
  • a fault tree for determining a failure is generated from system configuration information related to software and hardware, and whether the failure probability calculated based on the fault tree satisfies a reference value.
  • a method of analyzing whether or not is disclosed.
  • Patent Document 3 discloses a method of registering information on availability, functions, etc. as metadata when installing an application program or application service, and using it for subsequent analysis of configuration management, failure detection, diagnosis, recovery, and the like. ing.
  • Patent Document 4 each time a failure occurs, the time during which the failure has continued and the number of users who have not been able to use the service due to the failure are stored, and these data are accumulated so that the failure time ratio, user 1 A method for estimating the ratio of suffering a failure per person, the operation rate, and the like is disclosed.
  • Patent Documents 1 to 4 it is possible to analyze the operating rate and failure recovery time of the information processing system. For example, when an information processing system is newly operated, or when updating an information processing system that is in operation, such as expansion or review of the configuration, risks that affect multiple components (shared risk) are incorporated.
  • An availability prediction model can be created. Specifically, the data center manager can analyze the availability and failure recovery time of the information processing system by creating an availability prediction model incorporating a plurality of shared risks.
  • the present invention has been made in view of such circumstances, and an object thereof is to analyze the degree of influence of a risk that affects a plurality of components on the entire system.
  • a risk evaluation system is a risk information storage that stores a risk factor that may occur in an evaluation target system and a plurality of components in the evaluation target system that are affected by the risk factor in association with each other.
  • Each risk factor with reference to the characteristic information storage unit, the risk information storage unit, and the characteristic information storage unit that store the component, the component in the evaluation target system, and the characteristic information indicating the characteristic of the component in association with each other
  • an influence degree calculating unit that calculates the influence degree of each risk factor on the availability of the evaluation target system based on the characteristic information of a plurality of constituent elements affected by.
  • the computer associates a risk factor that may occur in the evaluation target system with a plurality of components in the evaluation target system that are affected by the risk factor.
  • Store in the risk information storage unit store the component in the evaluation target system and the characteristic information indicating the characteristic of the component in the characteristic information storage unit, and refer to the risk information storage unit and the characteristic information storage unit.
  • the degree of influence of each risk factor on the availability of the evaluation target system is calculated based on the characteristic information of a plurality of constituent elements affected by each risk factor.
  • the program according to one aspect of the present invention relates to a risk information by associating a risk factor that may occur in the evaluation target system with a plurality of components in the evaluation target system that are affected by the risk factor.
  • a function for storing the function stored in the storage unit, the component in the evaluation target system, and the characteristic information indicating the characteristic of the component in the characteristic information storage unit, the risk information storage unit, and the characteristic information storage unit And a function for calculating the degree of influence of each risk factor on the availability of the evaluation target system based on the characteristic information of a plurality of components affected by each risk factor.
  • the “unit” does not simply mean a physical means, but includes a case where the function of the “unit” is realized by software. Also, even if the functions of one “unit” or device are realized by two or more physical means or devices, the functions of two or more “units” or devices are realized by one physical means or device. May be.
  • FIG. 1 is a diagram showing a configuration of a risk evaluation system according to an embodiment of the present invention.
  • the risk evaluation system 10 is a system for evaluating the degree of availability of risk factors that may occur in an evaluation target system that is an information processing system to be evaluated, and uses one or a plurality of information processing apparatuses. Composed. As shown in FIG. 1, the risk evaluation system 10 includes a risk information input unit 20, a risk information storage unit 22, a characteristic information input unit 24, a characteristic information storage unit 26, an influence degree calculation unit 28, an influence degree storage unit 30, and An influence output unit 32 is included. Each unit in the risk evaluation system 10 can be realized, for example, by using a storage area such as a memory or a storage device or by executing a program stored in the storage area by a processor.
  • FIG. 2 shows an example of the evaluation target system.
  • the evaluation target system 50 includes physical servers 52 and 54, a router 56, and a power supply 58.
  • the physical servers 52 and 54 are server devices that physically exist.
  • the identifier of the physical server 52 is “X” and the identifier of the physical server 54 is “Y”, which are also represented as the physical server X and the physical server Y, respectively.
  • the physical server 52 is configured to be able to execute a hypervisor 60 and virtual servers 62 and 64.
  • the physical server 54 is configured to execute the virtual servers 70, 72, 74, and 76.
  • the identifiers of the virtual servers 60, 62, 64, 70, 72, 74, and 76 are sequentially set to “A”, “B”, “C”, “D”, “E”, and “F”. These are also expressed as virtual server A to virtual server F, respectively.
  • the router 56 is provided so that data communication is possible between the physical server X and the physical server Y.
  • the power source 58 is used to supply power to the physical servers 52 and 54 and the router 56.
  • the hypervisor 60 and the virtual servers A to F that are executed on the physical servers 52 and 54 also have a system configuration. Is an element.
  • the identifiers of the physical server and the virtual server have been described, the identifiers may be assigned to the components other than the physical server and the virtual server. The identifier may be any information as long as it can identify the component, such as a device name or a MAC (Media Access Control) address.
  • the risk information input unit 20 receives input of risk information necessary for evaluating risk factors in the evaluation target system 50.
  • the risk information input unit 20 can display a screen for inputting risk information on the display and accept risk information input via an input interface such as a keyboard.
  • the risk information input unit 20 stores the received risk information in the risk information storage unit 22.
  • the risk information input unit 20 can add risk information to the risk information storage unit 22 or can correct risk information already stored in the risk information storage unit 22.
  • the data format of the risk information stored in the risk information storage unit 22 is arbitrary.
  • the risk information may be held as a table in a relational database (RDB: Relational Database), or may be stored in a text format in a file.
  • RDB Relational Database
  • FIG. 3 shows an example of risk information stored in the risk information storage unit 22.
  • the risk information includes a risk factor and an identifier of a component that is affected by the risk factor.
  • the risk factor indicates an event that may affect the availability of the evaluation target system 50.
  • the risk factor “physical server X” indicates that a failure occurs in the physical server X.
  • the risk factor is not limited to a failure of a device or a software module, but can be any event as long as it may affect the availability of the evaluation target system 50.
  • each risk factor is associated with a plurality of component identifiers.
  • the risk factor “physical server X” is associated with component identifiers “A” and “B”. This indicates that when a failure occurs in the physical server X, the operations of the virtual server A and the virtual server B are stopped. That is, the risk factor “physical server X” affects the operation of the two virtual servers.
  • a risk factor that affects a plurality of components is also referred to as a “shared risk factor”.
  • all risk factors are shared risk factors, but the risk information storage unit 22 may store risk factors that affect only one component.
  • only the virtual server is shown as a component affected by the risk factor, but any component in the evaluation target system 50 can be a target affected by the risk factor.
  • the characteristic information input unit 24 receives characteristic information indicating the characteristics of the constituent elements for each constituent element of the evaluation target system 50.
  • the characteristic information input unit 24 can display a screen for inputting characteristic information on the display and can accept characteristic information input via an input interface such as a keyboard.
  • the characteristic information input unit 24 stores the received characteristic information in the characteristic information storage unit 26 in association with the identifier of the component.
  • the characteristic information input unit 24 can add the characteristic information to the characteristic information storage unit 26 or can correct the characteristic information stored in the characteristic information storage unit 26.
  • the data format of the characteristic information stored in the characteristic information storage unit 26 is arbitrary.
  • the characteristic information may be held as a table in a relational database (RDB), or may be stored in a text format in a file.
  • RDB relational database
  • FIG. 4 shows an example of characteristic information stored in the characteristic information storage unit 26.
  • the characteristic information includes a failure probability ( ⁇ ), a recovery probability ( ⁇ ), and an importance level.
  • the failure probability ( ⁇ ) is information indicating the failure characteristics of the component.
  • the information indicating the failure characteristics of the constituent elements is not limited to the failure probability, and for example, another index such as an average failure interval (MTBF) or the number of failures may be used.
  • the recovery probability ( ⁇ ) is information indicating characteristics of recovery from a component failure.
  • the information indicating the characteristics of recovery from a component failure is not limited to the recovery probability, and for example, another index such as an average recovery time (MTTR) or the number of times of recovery may be used.
  • MTTR average recovery time
  • the importance is an index indicating the importance of the component in the evaluation target system 50.
  • the importance of a virtual server used to provide an important service can be increased.
  • the importance of a physical server storing important data can be increased.
  • the greater the value the higher the importance. 4 shows only the characteristic information of virtual server A to virtual server F, the characteristic information of other components can be registered in the characteristic information storage unit 26 in the same manner.
  • the influence degree calculation unit 28 refers to the risk information storage unit 22 and the characteristic information storage unit 26, and determines each of the availability of the evaluation target system 50 based on the characteristic information of the constituent elements affected by each risk factor. Calculate the impact of risk factors. For example, the influence degree calculation unit 28 can determine the degree of influence of each risk factor by calculating the degree of influence on the availability of the evaluation target system 50 for each component affected by each risk factor. Then, the influence degree calculation unit 28 stores the calculated influence degree in the influence degree storage unit 30 in association with the risk factor.
  • the influence degree calculation unit 28 can calculate the influence degree for each component affected by each risk factor, and can determine the maximum value of the calculated influence degree as the influence degree by each risk factor. Specifically, the influence degree calculation unit 28 can calculate the influence degree due to each risk factor by, for example, the following equation (1).
  • Influence max ((1 / ⁇ i + 1 / ⁇ i ) ⁇ E i ) (1)
  • ⁇ i , ⁇ i , and E i indicate the failure probability, recovery probability, and importance of the component i affected by the risk factor.
  • the function max outputs the maximum value of the influence levels of all the constituent elements affected by the risk factor.
  • the influence degree of each component i is expressed as (1 / ⁇ i + 1 / ⁇ i ) ⁇ E i . “1 / ⁇ i ” in this expression indicates that the influence degree of the risk factor affecting the component that is difficult to fail is large.
  • “1 / ⁇ i ” indicates that the degree of influence of a risk factor that affects a component that is difficult to recover is large. Further, “E i ” represents that the influence degree of the risk factor that affects the component having high importance is large.
  • the impact calculation unit 28 calculates the impact for each component affected by each risk factor, and the maximum value of the calculated impact is affected by each risk factor. Can be determined as degrees.
  • the influence degree of the risk factor “physical server X” is calculated.
  • the components that are affected by the risk factor “physical server X” are “virtual server A” and “virtual server B”.
  • the failure probability, recovery probability, and importance of the virtual server A are 0.01, 0.95, and 0.8. If this is substituted into (1 / ⁇ i + 1 / ⁇ i ) ⁇ E i , the influence degree of the virtual server A becomes “81” (rounded off after the decimal point; the same applies hereinafter).
  • the influence degree of the virtual server B is “101”. Therefore, the influence degree calculation unit 28 determines “101” which is the maximum value among “81” and “101” as an influence degree by the risk factor “physical server X”. The influence degree calculation unit 28 calculates the influence degree due to other risk factors in the same procedure. The influence degree calculation unit 28 stores the influence degree thus calculated in the influence degree storage unit 30 in association with the risk factor. The result is shown in FIG.
  • the influence levels of the two risk factors “physical server X” and “hypervisor” are both “101”, and the influence value is the largest among the four risk factors. It has become. Therefore, according to the degree of influence calculated by the above equation (1), for example, two risk factors of “physical server X” and “hypervisor” are design issues that should be preferentially examined in the evaluation target system 50. Can be determined.
  • the influence value “101” due to the two risk factors “physical server X” and “hypervisor” is the influence degree of “virtual server B”. Therefore, it can be seen that the ripple effect that affects the “virtual server B” due to the risk factors of the “physical server X” and “hypervisor” is a design problem to be preferentially studied.
  • the influence degree calculation unit 28 stores the influence degree of each component affected by each risk factor in the influence degree storage unit 30 in addition to the influence degree by each risk factor. I can keep it.
  • the influence degree calculation unit 28 can calculate the influence degree for each component affected by each risk factor, and can determine the total value of the calculated influence degrees as the influence degree due to each risk factor. Specifically, the influence degree calculation unit 28 can calculate the influence degree due to each risk factor by, for example, the following equation (2).
  • Influence sum (1 / ⁇ i + 1 / ⁇ i ) ⁇ E i (2)
  • the function sum outputs the total value of the influence levels of all the constituent elements affected by the risk factor. That is, by using Equation (2), the impact calculation unit 28 calculates the impact for each component affected by each risk factor, and the total value of the calculated impact is affected by each risk factor. Can be determined as degrees.
  • the influence degree of the risk factor “physical server X” is calculated.
  • the components that are affected by the risk factor “physical server X” are “virtual server A” and “virtual server B”.
  • the influence degree calculation unit 28 determines “182” that is the total value of “81” and “101” as the influence degree by the risk factor “physical server X”.
  • the influence degree calculation unit 28 calculates the influence degree due to other risk factors in the same procedure.
  • the influence degree calculation unit 28 stores the influence degree thus calculated in the influence degree storage unit 30 in association with the risk factor. The result is shown in FIG.
  • the degree of influence by the risk factor of “Hypervisor” is “339”, and the value of the degree of influence is the largest among the four risk factors. Therefore, according to the degree of influence calculated by the above equation (2), for example, it can be determined that the risk factor of the “hypervisor” is a design problem that should be preferentially examined in the evaluation target system 50. .
  • the influence ratio of the “virtual server B” is the largest percentage of the influence degree value “339” due to the risk factor of the “hypervisor”. Therefore, it can be seen that the ripple effect that affects the “virtual server B” due to the risk factor of the “hypervisor” is a design issue to be preferentially examined.
  • the influence degree calculation unit 28 stores the influence degree of each component affected by each risk factor in the influence degree storage unit 30 in addition to the influence degree by each risk factor. I can keep it.
  • failure probability, recovery probability, and importance are used, but only one or two of these three indicators may be used. . Further, the failure probability, the recovery probability, and the degree of importance consideration (weighting) may be adjustable according to the characteristics of the evaluation target system 50. Further, in the case of Expressions (1) and (2), the value of the influence degree of each component i is (1 / ⁇ i + 1 / ⁇ i ) ⁇ E i, which is a fixed value regardless of the risk factor. . Therefore, the influence degree calculation unit 28 may calculate the influence degree of each component i in advance and store it in the characteristic information storage unit 26 as characteristic information.
  • the influence degree output unit 32 can output information indicating the influence degree with reference to the influence degree storage unit 30.
  • the influence degree output unit 32 may display the influence degree for each risk factor on the display as shown in FIGS.
  • the influence level output unit 32 may not output information on the degree of influence on all risk factors, but may output only information on some risk factors having a high degree of influence, for example.
  • the influence level output unit 32 does not output information indicating the degree of influence on the display, but outputs it via a network or outputs it to a storage medium in a data format that can be used in another information processing apparatus. It is good as well.
  • FIG. 7 is a flowchart showing an example of the influence degree calculation process in the risk evaluation system 20. This process is started at an arbitrary timing after the information input by the risk information input unit 20 and the characteristic information input unit 24 is performed, for example, in response to an instruction from the system administrator.
  • the influence degree calculation unit 28 determines whether there is a risk factor whose influence degree is not calculated among the risk factors stored in the risk information storage unit 22 (S701). When there is a risk factor for which the degree of influence has not been calculated (S701: YES), the degree-of-impact calculation unit 28 has a risk factor for which the degree of influence has not been calculated from the risk information storage unit 22, and a configuration in which the risk factor affects the risk factor.
  • the element identifier is read (S702). Then, the degree-of-influence calculation unit 28 reads out the characteristic information corresponding to the identifier from the characteristic information storage unit 26 with respect to the read identifier of each component (S703).
  • the influence degree calculation unit 28 calculates the influence degree of each risk factor based on the read characteristic information by, for example, Expression (1) or Expression (2) (S704), and uses the calculated influence degree as a risk factor.
  • the association is stored in the influence storage unit 30 (S705).
  • the above-described influence calculation processing (S702 to S705) is executed for all risk factors stored in the risk information storage unit 22. Then, when there is no risk factor for which the influence degree is not calculated (S701: NO), the influence degree output unit 32 refers to the influence degree storage unit 30 and outputs information on the risk factor and the influence degree (S706).
  • the risk information storage unit 22 stores risk factors that may occur in the evaluation target system 50 and a plurality of components that are affected by the risk factors in association with each other.
  • the characteristic information storage unit 26 stores the constituent elements in the evaluation target system 50 in association with the characteristic information indicating the characteristics of the constituent elements.
  • the degree-of-influence calculation unit 28 refers to the risk information storage unit 22 and the characteristic information storage unit 26, and determines each risk for the availability of the evaluation target system 50 based on the characteristic information of a plurality of components affected by each risk factor. The degree of influence of the factor can be calculated. Thereby, it becomes possible to analyze the influence degree of the risk which affects a some component on the whole system.
  • the characteristic information can include information indicating the characteristic of the failure of the component.
  • the influence degree calculation unit 28 can calculate the influence degree so that the influence degree is high for a risk factor that affects a component that is difficult to fail.
  • the characteristic information can include information indicating the characteristic of recovery from the failure of the component.
  • the influence degree calculation unit 28 can calculate the influence degree so that the influence degree is high for a risk factor that affects a component that is difficult to recover.
  • the characteristic information can include information indicating the importance of the component.
  • the influence degree calculation unit 28 can calculate the influence degree so that the influence degree is high for the risk factor that affects the component having high importance.
  • this embodiment is for making an understanding of this invention easy, and is not for limiting and interpreting this invention.
  • the present invention can be changed / improved without departing from the spirit thereof, and the present invention includes equivalents thereof.
  • the risk evaluation system 10 is configured as shown in FIG. 1, but the risk evaluation system 10 is configured only by the risk information storage unit 22, the characteristic information storage unit 26, and the influence degree calculation unit 28. It is also possible.
  • the risk information storage part which matches and memorize
  • the characteristic information storage unit that associates and stores the characteristic element indicating the characteristic of the component and the characteristic information storage unit, the risk information storage unit, and the characteristic information storage unit, and the plurality of risk factors affect each of the risk factors.
  • a risk evaluation system comprising: an influence degree calculation unit that calculates an influence degree of each risk factor on the availability of the evaluation target system based on the characteristic information of the constituent elements.
  • the said influence degree calculation part is the influence degree to the said evaluation object system of this risk factor about the total value of the calculated influence degree about each risk factor.
  • Risk assessment system. A computer matches the risk factor which may generate
  • a risk evaluation method of calculating an influence degree of each risk factor on the availability of the evaluation target system based on the characteristic information of the plurality of constituent elements (Additional remark 9)
  • stores it in a risk information storage part Refer to the risk information storage unit and the characteristic information storage unit, the function of storing the component in the evaluation target system and the characteristic information indicating the characteristic of the component in association with the characteristic information storage unit, the risk information storage unit and the characteristic information storage unit, A program for realizing a function of calculating the degree of influence of each risk factor on the availability of the evaluation target system based on the characteristic information of the plurality of constituent elements affected by the risk factor.

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Abstract

Le but de la présente invention consiste à analyser le degré auquel les risques affectant une pluralité d'éléments constitutifs affectent un système dans son ensemble. Des facteurs de risque potentiels dans un système à évaluer, et une pluralité d'éléments constitutifs affectés par les facteurs de risque dans le système à évaluer, sont associés les uns aux autres et stockés dans une unité de stockage d'informations de risques ; les éléments constitutifs dans le système à évaluer, et des informations caractéristiques, exprimant les caractéristiques des éléments constitutifs, sont associés les uns aux autres et stockés dans une unité de stockage d'informations caractéristiques ; l'unité de stockage d'informations de risque et l'unité de stockage d'informations caractéristiques sont consultées, et le degré auquel chaque facteur de risque affecte la disponibilité du système à évaluer, est calculé sur la base des informations de caractéristiques pour la pluralité des éléments constitutifs affectés par chaque facteur de risque.
PCT/JP2013/050065 2012-02-01 2013-01-08 Système d'évaluation de risque, procédé d'évaluation de risque, et programme WO2013114911A1 (fr)

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WO2015146081A1 (fr) * 2014-03-28 2015-10-01 日本電気株式会社 Appareil de gestion de risque, support d'enregistrement à programme de gestion de risque enregistré sur celui-ci et procédé de gestion de risque
JP2015191390A (ja) * 2014-03-28 2015-11-02 株式会社日立製作所 セキュリティ対処支援システム
CN116523313A (zh) * 2023-05-15 2023-08-01 北京中润惠通科技发展有限公司 一种作业安全智能监控系统
CN116523313B (zh) * 2023-05-15 2023-12-08 北京中润惠通科技发展有限公司 一种作业安全智能监控系统

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