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Swarm virus - Next-generation virus and antivirus paradigm?

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dc.title Swarm virus - Next-generation virus and antivirus paradigm? en
dc.contributor.author Zelinka, Ivan
dc.contributor.author Das, Swagatam
dc.contributor.author Sikora, Lubomír
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof Swarm and Evolutionary Computation
dc.identifier.issn 2210-6502 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2018
utb.relation.volume 43
dc.citation.spage 207
dc.citation.epage 224
dc.type article
dc.language.iso en
dc.publisher Elsevier
dc.identifier.doi 10.1016/j.swevo.2018.05.003
dc.relation.uri https://www.x-mol.com/paper/676558
dc.subject Swarm algorithms en
dc.subject Computer virus en
dc.subject Security en
dc.subject Identification en
dc.subject Evolutionary algorithms en
dc.subject Swarm malware en
dc.subject Swarm intelligence en
dc.subject Ant colony optimization en
dc.subject Complex network en
dc.description.abstract In this article, we outline a possible dynamics, structure, and a behavior of a hypothetical (up to now) swarm malware as a background for a future antimalware system. We suggest how to capture and visualize behavior of such malware when it walks through the file system of an operating system. The swarm virus prototype, designed here, mimics a swarm system behavior and thus follows the main idea underlying the swarm intelligence algorithms. The information of the prototype's behavior is stored and visualized in the form of a complex network, reflecting virus communication and swarm behavior. The network nodes are then individual virus instances. The network has certain properties associated with its structure that can be used by the virus instances in its activities like locating target and executing payload on the right object. As the paper shows, the swarm behavior pattern can be incorporated also to an antimalware systems, and can be analyzed for a future computer system protection. © 2018 Elsevier B.V. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1008372
utb.identifier.obdid 43879132
utb.identifier.scopus 2-s2.0-85048575754
utb.identifier.wok 000452933500011
utb.source j-scopus
dc.date.accessioned 2019-01-31T08:58:58Z
dc.date.available 2019-01-31T08:58:58Z
dc.description.sponsorship Grant Agency of the Czech Republic [GACR P103/15/06700S]; NPU I by the Ministry of Education of the Czech Republic [MSMT-7778/2014]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; COST Action [CA15140]; SGS, VSB-Technical University of Ostrava [SGS 2018/177]
utb.contributor.internalauthor Šenkeřík, Roman
utb.wos.affiliation [Zelinka, Ivan] Ton Duc Thang Univ, Fac Elect & Elect Engn, Modeling Evolutionary Algorithms Simulat & Artifi, Ho Chi Minh City, Vietnam; [Zelinka, Ivan; Sikora, Lubomir] VSB Tech Univ Ostrava, Fac Elect Engn & Comp Sci, Dept Comp Sci, Ostrava, Czech Republic; [Das, Swagatam] Indian Stat Inst, Elect & Commun Sci Unit, 203 BT Rd, Kolkata 700108, W Bengal, India; [Senkerik, Roman] Tomas Bata Univ Zlin, Fac Appl Informat, Nam TG Masaryka 5555, Zlin 76001, Czech Republic
utb.scopus.affiliation Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Viet Nam; Department of Computer Science Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Czech Republic; Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B.T. Road, Kolkata, W.B. 700108, India; Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, Zlin, 760 01, Czech Republic
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