Fractal methods for the representation and analysis of polymorphism in malware

Author

Cowen, Benn ; Shafi, Kamran

Author_Institution

Dept. of Defence, Canberra, ACT, Australia

fYear

2013

fDate

12-14 Nov. 2013

Firstpage

1

Lastpage

5

Abstract

The preponderance of network resident cyber threats are due to zero day vulnerabilities or unpatched systems. Traditional signature based detection methods are ineffective against such threats, and anomaly detection methods are typically computationally intensive. By treating polymorphism as a stochastic process and applying fractal visualization methods, identifying features can be found. These features are suited to then be used for detection with algorithms such as Bayes classifiers.

Keywords

data visualisation; fractals; invasive software; stochastic processes; Bayes classifiers; anomaly detection methods; feature identification; fractal visualization methods; malware; network resident cyber threats; polymorphism analysis; polymorphism representation; signature based detection methods; stochastic process; unpatched systems; zero day vulnerability; Chaos; Engines; Fractals; Games; Intrusion detection; Malware; Software; Computer security; Fractals; Intrusion detection; Random processes; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Military Communications and Information Systems Conference (MilCIS), 2013

Conference_Location

Canberra, ACT

Print_ISBN

978-1-4799-0281-1

Type

conf

DOI

10.1109/MilCIS.2013.6694490

Filename

6694490