TY - JOUR
T1 - A stochastic model of cyber attacks with imperfect detection
AU - Fang, Rui
AU - Li, Xiaohu
N1 - Publisher Copyright:
© 2019, © 2019 Taylor & Francis Group, LLC.
PY - 2020/5/2
Y1 - 2020/5/2
N2 - This paper introduces a cyber security model with imperfect detection, in which one attacker launches multiple attacks against the target with adjusted strength based on the previous attacking outcome. Several sufficient conditions leading to the usual stochastic order on the first time to observe a truly compromised target, to observe a successful attack and to compromise the target are developed, respectively. The probability for the target to be truly compromised before observing some number of successful attacks is proved to increase (decrease) in the attacking (defense) strength. Monte Carlo simulations are also conducted to empirically illustrate the theoretical results.
AB - This paper introduces a cyber security model with imperfect detection, in which one attacker launches multiple attacks against the target with adjusted strength based on the previous attacking outcome. Several sufficient conditions leading to the usual stochastic order on the first time to observe a truly compromised target, to observe a successful attack and to compromise the target are developed, respectively. The probability for the target to be truly compromised before observing some number of successful attacks is proved to increase (decrease) in the attacking (defense) strength. Monte Carlo simulations are also conducted to empirically illustrate the theoretical results.
KW - First hitting time
KW - hidden Markov chain
KW - stochastic order
KW - strong dominance
KW - sub-probability transition matrix
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U2 - 10.1080/03610926.2019.1568489
DO - 10.1080/03610926.2019.1568489
M3 - Article
AN - SCOPUS:85061058048
SN - 0361-0926
VL - 49
SP - 2158
EP - 2175
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 9
ER -