Honeypot trace forensics: The observation viewpoint matters

Van Hau Pham, Marc Dacier

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

In this paper, we propose a method to identify and group together traces left on low interaction honeypots by machines belonging to the same botnet(s) without having any a priori information at our disposal regarding these botnets. In other words, we offer a solution to detect new botnets thanks to very cheap and easily deployable solutions. The approach is validated thanks to several months of data collected with the worldwide distributed Leurr.com system. To distinguish the relevant traces from the other ones, we group them according to either the platforms, i.e. targets hit or the countries of origin of the attackers. We show that the choice of one of these two observation viewpoints dramatically influences the results obtained. Each one reveals unique botnets. We explain why. Last but not the least, we show that these botnets remain active during very long periods of times, up to 700 days, even if the traces they left are only visible from time to time.1 © 2010 Elsevier B.V. All rights reserved.
Original languageEnglish (US)
Pages (from-to)539-546
Number of pages8
JournalFuture Generation Computer Systems
Volume27
Issue number5
DOIs
StatePublished - May 1 2011
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2022-09-12

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Computer Networks and Communications

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