Published January 2018 | Version v1
Journal article

Defending a cyber system with early warning mechanism

  • 1. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu (China)
  • 2. Department of Mathematics, Illinois State University, Normal, IL (United States)
  • 3. Department of Computer Science, University of Houston, Houston, TX (United States)

Description

Highlights: • We consider an important mechanism of early warning for defending a cyber system that has become a key component of constructing network defense in practice. • The reliability function of a system under attack from one or multiple sources is derived. • We propose the optimal strategy for defending a cyber system with early warning components in the worst attack scenario. - Abstract: Due to the increasing reliance on networks, defending a cyber system is of vital importance. In this paper, we consider an important mechanism of early warning for defending a cyber system that has become a key component of constructing network defense in practice. We study the reliability of a system under attack from single or multiple sources. In particular, we discuss the effect of an early warning mechanism on the system reliability. We then propose the optimal strategy for defending a cyber system with early warning components in the worst attack scenario. The theoretical results are further validated by simulation evidence.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.ress.2017.08.021

Additional details

Identifiers

DOI
10.1016/j.ress.2017.08.021;
PII
S0951-8320(17)30105-9;

Publishing Information

Journal Title
Reliability Engineering and System Safety
Journal Volume
169
Journal Page Range
p. 224-234
ISSN
0951-8320
CODEN
RESSEP

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
49091358
Subject category
S42: ENGINEERING;
Descriptors DEI
NATIONAL DEFENSE; OPTIMIZATION; RELIABILITY

Optional Information

Copyright
Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.