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Malicious Code Detection Using Penalized Splines on OPcode Frequency

Date

Authors

Alazab, Mamoun

Kadiri, Mohammad

Venkatraman, S

Al-Nemrat, A

Publisher

Conference Organising Committee

Abstract

Recently, malicious software are gaining exponential growth due to the innumerable obfuscations of extended x86 IA-32 (OPcodes) that are being employed to evade from traditional detection methods. In this paper, we design a novel distinguisher to separate

Keywords

Keywords: Cybercrime; Malware detection; Multivariate statistics; Obfuscation; Operation codes; Logistics; Regression analysis; Reverse engineering; Computer crime Cybercrime; Malware detection; Multivariate statistics; Obfuscation; Operation codes; Penalised splines

URI

http://hdl.handle.net/1885/81310

Collections

ANU Research Publications

Source

Proceedings - 2012 3rd Cybercrime and Trustworthy Computing Workshop, CTC 2012

Type

Conference paper

DOI

10.1109/CTC.2012.15

Restricted until

2037-12-31

Downloads

File

Description

01_Alazab_Malicious_Code_Detection_Using_2013.pdf (130.87 KB)

02_Alazab_Malicious_Code_Detection_Using_2013.pdf (411.6 KB)