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Author:

Su, Kaile (Su, Kaile.) | Zhao, Congxin (Zhao, Congxin.) | Lv, Guanfeng (Lv, Guanfeng.) | Lin, Han (Lin, Han.) | Chen, Qingliang (Chen, Qingliang.)

Indexed by:

EI Scopus

Abstract:

Intrusion tolerance is an emerging network security technique, which enables the victim server systems to continue offering services (or degraded services) after being attacked. A state transition model has been presented to describe the dynamic behaviors of intrusion tolerant systems. In this paper, we build an attack finite state system based on the recent network attacks, and use SMV, a model checking tool, to analyze the intrusion tolerant systems by the interaction of the system model and the attack model. The analysis results demonstrate that not all types of attacks can be mapped to the system model. We improve this state transition model, whose correctness is proved by SMV. In addition, we give two attack instances mapped to our improved model. © Springer-Verlag Berlin Heidelberg 2005.

Keyword:

Fault tolerant computer systems Finite automata Error correction Security of data Mathematical models Servers Computer networks

Author Community:

  • [ 1 ] [Su, Kaile]Department of Computer Science, Sun Yat-sen University, Guangzhou 510275, China
  • [ 2 ] [Su, Kaile]Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, QLD 4111, Australia
  • [ 3 ] [Zhao, Congxin]Department of Computer Science, Sun Yat-sen University, Guangzhou 510275, China
  • [ 4 ] [Lv, Guanfeng]College of Computer Science, Beijing University of Technology, Beijing 100022, China
  • [ 5 ] [Lin, Han]Department of Computer Science, Sun Yat-sen University, Guangzhou 510275, China
  • [ 6 ] [Chen, Qingliang]Department of Computer Science, Sun Yat-sen University, Guangzhou 510275, China

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Source :

ISSN: 0302-9743

Year: 2005

Volume: 3828 LNCS

Page: 391-404

Language: English

JCR Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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