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Metamorphic malware detection based on support vector machine classification of malware sub-signatures

Achieving accurate and efficient metamorphic malware detection remains a challenge. Metamorphic malware is able to mutate and alter its code structure in each infection that can circumvent signature matching detection. However, some vital functionalities and code segments remain unchanged between mu...

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書誌詳細
主要な著者:	Khammas, Ban Mohammed, Monemi, Alireza, Ismail, Ismahani, Mohd. Nor, Sulaiman, Marsono, Muhammad Nadzir
フォーマット:	論文
言語:	English
出版事項:	Universitas Ahmad Dahlan 2016
主題:	TK Electrical engineering. Electronics Nuclear engineering
オンライン･アクセス:	http://eprints.utm.my/id/eprint/71495/1/IsmahaniIsmail2016_Metamorphicmalwaredetectionbasedon.pdf http://eprints.utm.my/id/eprint/71495/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994645699&doi=10.12928%2ftelkomnika.v14.i3.3850&partnerID=40&md5=9bddd91d72dd3d7765283346cee06803
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