Exploring Timeline-Based Malware Classification - Security and Privacy Protection in Information Processing Systems Access content directly
Conference Papers Year : 2013

Exploring Timeline-Based Malware Classification

Abstract

Over the decades or so, Anti-Malware (AM) communities have been faced with a substantial increase in malware activity, including the development of ever-more-sophisticated methods of evading detection. Researchers have argued that an AM strategy which is successful in a given time period cannot work at a much later date due to the changes in malware design. Despite this argument, in this paper, we convincingly demonstrate a malware detection approach, which retains high accuracy over an extended time period. To the best of our knowledge, this work is the first to examine malware executables collected over a span of 10 years.  By combining both static and dynamic features of malware and cleanware, and accumulating these features over intervals in the 10-year period in our test, we construct a high accuracy malware detection method which retains almost steady accuracy over the period. While the trend is a slight down, our results strongly support the hypothesis that perhaps it is possible to develop a malware detection strategy that can work well enough into the future.
Fichier principal
Vignette du fichier
978-3-642-39218-4_1_Chapter.pdf (1.71 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01463831 , version 1 (09-02-2017)

Licence

Attribution

Identifiers

Cite

Rafiqul Islam, Irfan Altas, Md. Saiful Islam. Exploring Timeline-Based Malware Classification. 28th Security and Privacy Protection in Information Processing Systems (SEC), Jul 2013, Auckland, New Zealand. pp.1-13, ⟨10.1007/978-3-642-39218-4_1⟩. ⟨hal-01463831⟩
401 View
209 Download

Altmetric

Share

Gmail Facebook X LinkedIn More