Kontaktujte nás | Jazyk: čeština English
Název: | Neural swarm virus | ||||||||||
Autor: | Truong, Thanh Cong; Zelinka, Ivan; Šenkeřík, Roman | ||||||||||
Typ dokumentu: | Článek ve sborníku (English) | ||||||||||
Zdrojový dok.: | Communications in Computer and Information Science. 2020, vol. 1092 CCIS, p. 122-134 | ||||||||||
ISSN: | 1865-0929 (Sherpa/RoMEO, JCR) | ||||||||||
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ISBN: | 978-3-03-037837-0 | ||||||||||
DOI: | https://doi.org/10.1007/978-3-030-37838-7_12 | ||||||||||
Abstrakt: | 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. © Springer Nature Switzerland AG 2020. | ||||||||||
Plný text: | https://link.springer.com/chapter/10.1007/978-3-030-37838-7_12 | ||||||||||
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