Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/1828
Title: Development of Secure Antivirus with the Artificial Immune System Model
Authors: Waziri, Victor Onomza
Alhassan, J. K.
Olalere, Morufu
Abdulkadir, Adamu
Keywords: Secure Plus, Polymorphism, Metamorphism, Metamorphism, artificial immune system
Issue Date: 2015
Publisher: International Journal of Innovative Technology and Research
Citation: https://www.ijier.net/ijier
Series/Report no.: Volume 3 Number 2;
Abstract: This paper is about Malware proliferation in the wide and the development of an Antivirus called Secure Plus. Malware is a generic name for malfunctioned program codes that could wreak destructive impacts on Information Technology critical infrastructures. These malware usually use various techniques to avoid being detected; usually they are encrypted using hybridized cryptographic algorithms. Malware may be detected using antivirus that can scan the database signatures already accumulated and stored by antivirus vendors in some server. These stored databases signatures can then be compared with zero-day malware through comparison with the benign software. The zero-day malware are of sophisticated program codes that can transmute into different transforming patterns; yet retain their portent functionalities attributes and are now of billion categories by deverse clones. This paper after over viewing the literatures on ground (and they are of large numerical numbers), attempts to make its contribution to the design and development of Antivirus that can detect those zero-day or metamorphic malware. This proposed Antivirus being developed is christened Secure Plus that applies the heuristic Artificial Immune System Algorithm for the design and development. The tested experimental outputs are provided as prove of the Secure Plus effectual functionality worthy of application but need further works through to detect malware proactively
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/1828
ISSN: 2411-2933
Appears in Collections:Computer Science

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