Behavioral Malware Detection by Data Mining - Brossura

Ninyesiga, Allan; Ngubiri, John

 
9786139923069: Behavioral Malware Detection by Data Mining
Brossura
ISBN 10: 6139923069 ISBN 13: 9786139923069
Casa editrice: LAP LAMBERT Academic Publishing, 2018

Sinossi

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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Editore
LAP LAMBERT Academic Publishing
Data di pubblicazione
2018
Lingua
Inglese
ISBN 10 
6139923069
ISBN 13 
9786139923069
Rilegatura
Copertina flessibile
Numero di pagine
96
Contatto del produttore
non disponibile
Persona responsabile
KreGa Onlinehandel GmbH
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