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X-ware: a proof of concept malware utilizing artificial intelligence

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F22%3A10249262" target="_blank" >RIV/61989100:27740/22:10249262 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27240/22:10249262

  • Result on the web

    <a href="http://ijece.iaescore.com/index.php/IJECE/article/view/25216/15582" target="_blank" >http://ijece.iaescore.com/index.php/IJECE/article/view/25216/15582</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.11591/ijece.v12i2.pp1937-1944" target="_blank" >10.11591/ijece.v12i2.pp1937-1944</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    X-ware: a proof of concept malware utilizing artificial intelligence

  • Original language description

    Recent years have witnessed a dramatic growth in utilizing computational intelligence techniques for various domains. Coherently, malicious actors are expected to utilize these techniques against current security solutions. Despite the importance of these new potential threats, there remains a paucity of evidence on leveraging these research literature techniques. This article investigates the possibility of combining artificial neural networks and swarm intelligence to generate a new type of malware. We successfully created a proof of concept malware named X-ware, which we tested against the Windows-based systems. Developing this proof of concept may allow us to identify this potential threat&apos;s characteristics for developing mitigation methods in the future. Furthermore, a method for recording the virus&apos;s behavior and propagation throughout a file system is presented. The proposed virus prototype acts as a swarm system with a neural network-integrated for operations. The virus&apos;s behavioral data is recorded and shown under a complex network format to describe the behavior and communication of the swarm. This paper has demonstrated that malware strengthened with computational intelligence is a credible threat. We envisage that our study can be utilized to assist current and future security researchers to help in implementing more effective countermeasures. (C) 2022 Institute of Advanced Engineering and Science. All rights reserved.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    International Journal of Electrical and Computer Engineering

  • ISSN

    2088-8708

  • e-ISSN

  • Volume of the periodical

    12

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    ID - INDONESIA

  • Number of pages

    8

  • Pages from-to

    1937-1944

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85122778849