Network Security Situation Assessment Based on Hidden Semi-Markov Model

2011 ◽  
pp. 509-516 ◽  
Author(s):  
Boyun Zhang ◽  
Zhigang Chen ◽  
Xiai Yan ◽  
Shulin Wang ◽  
Qiang Fan
Keyword(s):  
Network Security ◽  
Markov Model ◽  
Situation Assessment

scholarly journals A Markov-Based Intrusion Tolerance Finite Automaton

2021 ◽  
Vol 28 (2) ◽  
pp. 89-100
Keyword(s):  
Network Security ◽  
Markov Model ◽  
Finite Automaton ◽  
Network Services ◽  
Intrusion Tolerance ◽  
Security Strategy ◽  
Automatic Learning ◽  
Learning Mechanism ◽  
Proposed Model ◽  
Tolerance Model

It is inevitable for networks to be invaded during operation. The intrusion tolerance technology comes into being to enable invaded networks to provide the necessary network services. This paper introduces an automatic learning mechanism of the intrusion tolerance system to update network security strategy, and derives an intrusion tolerance finite automaton model from an existing intrusion tolerance model. The proposed model was quantified by the Markov theory to compute the stable probability of each state. The calculated stable probabilities provide the theoretical guidance and basis for administrators to better safeguard network security. Verification results show that it is feasible, effective, and convenient to integrate the Markov model to the intrusion tolerance finite automaton.

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