Openly accessible

Function length as a tool for malware classification

Tian, R., Batten, L. M. and Versteeg, S. C. 2008, Function length as a tool for malware classification, in Proceedings of the 3rd International Conference on Malicious and Unwanted Software : MALWARE 2008, IEEE, Los Alamitos, Calif., pp. 69-76.

Attached Files
Name Description MIMEType Size Downloads
batten-functionlengthasatool-2008.pdf Published version application/pdf 305.60KB 330

Title Function length as a tool for malware classification
Author(s) Tian, R.
Batten, L. M.
Versteeg, S. C.
Conference name MALWARE : International Conference on Malicious and Unwanted Software (3rd : 2008 : Alexandria, Va.)
Conference location Alexandria, Va.
Conference dates 7-8 October 2008
Title of proceedings Proceedings of the 3rd International Conference on Malicious and Unwanted Software : MALWARE 2008
Editor(s) [Unknown]
Publication date 2008
Conference series Malicious and Unwanted Software Conference
Start page 69
End page 76
Publisher IEEE
Place of publication Los Alamitos, Calif.
Keyword(s) Trojans
function length
malware classification
malware proliferation
invasive software
Summary The proliferation of malware is a serious threat to computer and information systems throughout the world. Antimalware companies are continually challenged to identify and counter new malware as it is released into the wild. In attempts to speed up this identification and response, many researchers have examined ways to efficiently automate classification of malware as it appears in the environment. In this paper, we present a fast, simple and scalable method of classifying Trojans based only on the lengths of their functions. Our results indicate that function length may play a significant role in classifying malware, and, combined with other features, may result in a fast, inexpensive and scalable method of malware classification.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 9781424432899
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
HERDC Research category E1 Full written paper - refereed
HERDC collection year 2008
Copyright notice ©2008, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30018116

Document type: Conference Paper
Collections: School of Engineering and Information Technology
Open Access Collection
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 15 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 419 Abstract Views, 330 File Downloads  -  Detailed Statistics
Created: Fri, 14 Aug 2009, 14:05:00 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.