DocumentCode :
1967261
Title :
Markov Model of Malicious Code Propagation
Author :
Peifeng Wang ; Shang Meng ; Hui Zhang ; Jichao Wang
Author_Institution :
Coll. of Inf. Sci. & Eng., HeBei Univ. of Sci. & Technol., Shijiazhuang, China
fYear :
2010
fDate :
30-31 Jan. 2010
Firstpage :
260
Lastpage :
263
Abstract :
In this paper, propagation process of malicious code in computer networks are analyzed by discrete-state Markov model. Computer system without defense mechanism of virus in the networks can be classified: susceptible(S), quarantine(Q), infection(I) and health(H). But the state of computer system is varying. These varieties are only relative to the state at present, and are disrelated to the past state. That is, it is Markovian. So it is appropriate to analysis the propagation process of malicious code in computer networks with Markov model. The model introduced in this paper is a kind of discrete finite-Markovian process. In this method, the transition probability between various state and the one step transition probability matrix can be obtained under given initial, thereby stationary state can be calculated after several step transition. Then the property of all kinds of states is analyzed later. From these the distribution of stationary state has nothing to do with the distribution of inceptive state, and once achieving stationary state, the state don´t change any more almost. In this paper the passage time of the stationary state has been gotten based on the property of all kinds of states also, it is very helpful to defense the malicious code.
Keywords :
Markov processes; codes; computer viruses; matrix algebra; probability; computer networks; discrete-state Markov model; health; infection; malicious code propagation; network virus; quarantine; susceptible computer system; transition probability matrix; Computer crime; Computer networks; Computer worms; Differential equations; Educational institutions; Information science; Marine technology; Probability; Stationary state; Underwater communication; Markov chain; Stochastic process; Transition Probability Matrix; equilibrium vector; the passage time;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing & Communication, 2010 Intl Conf on and Information Technology & Ocean Engineering, 2010 Asia-Pacific Conf on (CICC-ITOE)
Conference_Location :
Macao
Print_ISBN :
978-1-4244-5634-5
Electronic_ISBN :
978-1-4244-5635-2
Type :
conf
DOI :
10.1109/CICC-ITOE.2010.72
Filename :
5439218
Link To Document :
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