Network survivability modeling

Heegaard, Poul E.; Trivedi, Kishor S.

doi:10.1016/j.comnet.2009.02.014

Cited by 145 publications

(73 citation statements)

References 21 publications

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“…While Value-at-Risk was postulated to be used in communications networks for risk quantification in network security [20,21] and resilience [8,9], there are no efficient theoretical models to predict VaR when it is applied in network resilience. At the modelling level, we use some elements of the methodology similar to more recent works on network reliability, such as [22][23][24][25], yet we also deal with the modelling of whole distributions, and we add penalty [26], SLA [27,28], and compensation policy [8] concerns.…”

Section: Related Workmentioning

confidence: 99%

Effective Risk Assessment in Resilient Communication Networks

2016

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The paper discusses business impact analysis in the context of resilient communication networks. It is based on the total (aggregated) penalty that may be paid by an operator when the services (identified with transport demands) provided are interrupted due to network failures. The level of penalty is expressed as a commonly accepted business risk measure, Value-at-Risk (VaR). First, the main concern over VaR, namely the theoretical lack of subadditivity, is discussed. The study shows that, in practice, disadvantages do not appear in resilient network design, and VaR can be used without the need to apply more complex and less informative measures. Second, a method for calculating the upper bound of the total penalty is presented. The assessment is performed for unprotected and protected services with a broad variety of compensation policies used to translate technical loss to monetarily expressed penalty. The proposed bounds are experimentally shown to be effective in comparison with alternative calculation methods, and also in the case when some of the assumptions taken during the modelling stage are not met.

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Section: Related Workmentioning

confidence: 99%

Effective Risk Assessment in Resilient Communication Networks

2016

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“…It has been quantified by using multidimensional Markov chains to consider simultaneous failures [12]. In this paper, we define the survivability metric as the conditional success probability for one request provided that the agreement is failed at the first round.…”

Section: Survivability Metricmentioning

confidence: 99%

Survivability Analysis of VM-Based Intrusion Tolerant Systems

Zheng

Okamura

2015

IEICE Trans. Inf. & Syst.

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SUMMARYSurvivability is the capability of a system to provide its services in a timely manner even after intrusion and compromise occur. In this paper, we focus on the quantitative analysis of survivability of virtual machine (VM) based intrusion tolerant system in the presence of Byzantine failures due to malicious attacks. Intrusion tolerant system has the ability of a system to continuously provide correct services even if the system is intruded. This paper introduces a scheme of the intrusion tolerant system with virtualization, and derives the success probability for one request by a Markov chain under the environment where VMs have been intruded due to a security hole by malicious attacks. Finally, in numerical experiments, we evaluate the performance of VM-based intrusion tolerant system from the viewpoint of survivability. key words: intrusion tolerant system, byzantine failure, virtualization, survivability, Markov model

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“…Heegaard et al demonstrate modeling approaches including stochastic reward nets and continuous time Markov chain to quantify network survivability and clarify the tradeoffs regarding the cost of changing, extending and solving models [39], [40]. Our modeling quantifies the system behavior with the probability distribution on post states.…”

Section: Related Workmentioning

confidence: 99%

Investigating System Survivability from a Probabilistic Perspective

Zhao

Huang

Qin

et al. 2014

IEICE Trans. Inf. & Syst.

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SUMMARYSurvivability is an essential requirement of the networked information systems analogous to the dependability. The definition of survivability proposed by Knight in [16] provides a rigorous way to define the concept. However, the Knight's specification does not provide a behavior model of the system as well as a verification framework for determining the survivability of a system satisfying a given specification. This paper proposes a complete formal framework for specifying and verifying the concept of system survivability on the basis of Knight's research. A computable probabilistic model is proposed to specify the functions and services of a networked information system. A quantified survivability specification is proposed to indicate the requirement of the survivability. A probabilistic refinement relation is defined to determine the survivability of the system. The framework is then demonstrated with three case studies: the restaurant system (RES), the Warship Command and Control system (LWC) and the Command-and-Control (C2) system.

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Network survivability modeling

Cited by 145 publications

References 21 publications

Effective Risk Assessment in Resilient Communication Networks

Effective Risk Assessment in Resilient Communication Networks

Survivability Analysis of VM-Based Intrusion Tolerant Systems

Investigating System Survivability from a Probabilistic Perspective

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