A semi-Markov survivability evaluation model for intrusion tolerant database systems

Alex Hai Wang, Su Yan, Peng Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Survivability modeling and evaluation have gained increasing importance. Most existing models assume that the distributions for transitions between states are exponential. However, this assumption does not hold in many real cases. To address this problem, we propose a novel semi-Markov survivability evaluation model, which allows the transitions between states to follow nonexponential distributions. Novel quantitative measures are also proposed to characterize the capability of a resilient system in surviving intrusions. Model validation, which is possibly the most important step in the life cycle of model development, is largely overlooked in previous research. In this paper, a real intrusion tolerant database system ITDB is implemented to validate the proposed statespace models. Empirical experiments show that the semi-Markov model predicts the system behaviors with high accuracy. Furthermore, in this paper we evaluate the impact of intrinsic system deficiencies and attack behaviors on the survivability of intrusion tolerant database systems.

Original languageEnglish (US)
Title of host publicationARES 2010 - 5th International Conference on Availability, Reliability, and Security
Pages104-111
Number of pages8
DOIs
StatePublished - 2010
Event5th International Conference on Availability, Reliability, and Security, ARES 2010 - Krakow, Poland
Duration: Feb 15 2010Feb 18 2010

Publication series

NameARES 2010 - 5th International Conference on Availability, Reliability, and Security

Other

Other5th International Conference on Availability, Reliability, and Security, ARES 2010
Country/TerritoryPoland
CityKrakow
Period2/15/102/18/10

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Safety, Risk, Reliability and Quality

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