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Malware Detection

Malware Detection

Paperback

NetworkingComputer Security

ISBN10: 396067208X
ISBN13: 9783960672081
Publisher: Anchor Academic Publishing
Published: Dec 12 2017
Pages: 72
Weight: 0.21
Height: 0.15 Width: 5.83 Depth: 8.27
Language: English
In the present work the behavior of malicious software is studied, the security challenges are understood, and an attempt is made to detect the malware behavior automatically using dynamic approach. Various classification techniques are studied. Malwares are then grouped according to these techniques and malware with unknown characteristics are clustered into an unknown group. The classifiers used in this research are k-Nearest Neighbors (kNN), J48 Decision Tree, and n-grams.

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