Behavioral Malware Detection by Data Mining

Language: English

Published by LAP LAMBERT Academic Publishing, 2018

6139923069 / 9786139923069

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Malware cases are increasing both in numbers and fatality. Hackers design malware to compromise systems security mostly confidentiality, integrity, and availability. Malware elimination techniques exist but the malware must be detected first. Malware detection techniques still have weaknesses of high false positive/negatives rates. The emergency of polymorphic malware has made the situation worse. Recent studies have shown data mining to be promising in identifying malware by analyzing API calls. However, in this approach, a file is detected as malicious or not. It is not classified on to which malware class it belongs. This makes its elimination harder as elimination schemes are mostly class based. Classification as a post detection process is important if the malware is to be eliminated from the system. We experiment on the use of data mining approach to classify malware using 4-gram API system calls. We use Windows Portable Executables (PE) with their corresponding API calls. Using the Cuckoo sandbox. Relevant 4-gram API call features are extracted using Term Frequency-Inverse Document Frequency(TF-IDF). Machine Learning algorithms are then applied to classify the malware.

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Title
Behavioral Malware Detection by Data Mining
Author
John Ngubiri
Publisher
LAP LAMBERT Academic Publishing
Publication year
2018
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6139923069
ISBN 13
9786139923069
Item weight
161 grams
Dimensions
220x150x7 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

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