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Distributed Malware Detection System Based on Decentralized Architecture in Local Area Networks

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Advances in Intelligent Systems and Computing III (CSIT 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 871))

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Abstract

The paper proposes the architecture of a distributed malware detection system based on decentralized architecture in local area computer networks. Its feature is the synthesis of its requirements of distribution, decentralization, multilevel. This allows you to use it autonomously. In addition, the feature of the components of the system is the same organization, which allows the exchange of knowledge in the middle of the system, which, unlike the known systems, allows you to use the knowledge gained by separate parts of the system in other parts. The developed system allows to fill it with subsystems of detection of various types of malicious software in local area networks. The paper presents the results of experiments on the use of the developed system for the detection of metamorphic viruses.

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Author information

Authors and Affiliations

  1. Missouri University of Science and Technology, Rolla, USA

    George Markowsky

  2. Khmelnitsky National University, Khmelnitsky, Ukraine

    Oleg Savenko

  3. Kazimierz Pulaski University of Technology and Humanities, Radom, Poland

    Anatoliy Sachenko

  4. Ternopil National Economic University, Ternopil, Ukraine

    Anatoliy Sachenko

Authors
  1. George Markowsky
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  2. Oleg Savenko
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  3. Anatoliy Sachenko
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Corresponding author

Correspondence to George Markowsky .

Editor information

Editors and Affiliations

  1. Lviv Polytechnic National University, Lviv, Ukraine

    Natalia Shakhovska

  2. Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, Ukraine

    Mykola O. Medykovskyy

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Markowsky, G., Savenko, O., Sachenko, A. (2019). Distributed Malware Detection System Based on Decentralized Architecture in Local Area Networks. In: Shakhovska, N., Medykovskyy, M. (eds) Advances in Intelligent Systems and Computing III. CSIT 2018. Advances in Intelligent Systems and Computing, vol 871. Springer, Cham. https://doi.org/10.1007/978-3-030-01069-0_42

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