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Neural Swarm Virus

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Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing (SEMCCO 2019, FANCCO 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1092))

Abstract

The dramatic improvements in computational intelligence techniques over recent years have influenced many domains. Hence, it is reasonable to expect that virus writers will taking advantage of these techniques to defeat existing security solution. In this article, we outline a possible dynamic swarm smart malware, its structure, and functionality as a background for the forthcoming anti-malware solution. We propose how to record and visualize the behavior of the virus when it propagates through the file system. Neural swarm virus prototype, designed here, simulates the swarm system behavior and integrates the neural network to operate more efficiently. The virus’s behavioral information is stored and displayed as a complex network to reflect the communication and behavior of the swarm. In this complex network, every vertex is then individual virus instances. Additionally, the virus instances can use certain properties associated with the network structure to discovering target and executing a payload on the right object.

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Acknowledgement

The following grants are acknowledged for the financial support provided for this research: Grant of SGS No. SP2019/137, VSB Technical University of Ostrava. This work was also supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014), further by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 2172/15, 708 00, Ostrava-Poruba, Czech Republic

    Thanh Cong Truong & Ivan Zelinka

  2. Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01, Zlin, Czech Republic

    Roman Senkerik

Authors
  1. Thanh Cong Truong
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  2. Ivan Zelinka
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  3. Roman Senkerik
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Correspondence to Thanh Cong Truong .

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Editors and Affiliations

  1. University of Maribor, Maribor, Slovenia

    Aleš Zamuda

  2. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

  3. Division of Control and Instrumentation, Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  4. Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, Delhi, India

    Bijaya Ketan Panigrahi

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Truong, T.C., Zelinka, I., Senkerik, R. (2020). Neural Swarm Virus. In: Zamuda, A., Das, S., Suganthan, P., Panigrahi, B. (eds) Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing. SEMCCO FANCCO 2019 2019. Communications in Computer and Information Science, vol 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-37838-7_12

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  • DOI: https://doi.org/10.1007/978-3-030-37838-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37837-0

  • Online ISBN: 978-3-030-37838-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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