• 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