Towards situational awareness of large-scale botnet probing events

Zhichun Li*, Anup Goyal, Yan Chen, Vern Paxson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

Botnets dominate today's attack landscape. In this work, we investigate ways to analyze collections of malicious probing traffic in order to understand the significance of large-scale botnet probes. In such events, an entire collection of remote hosts together probes the address space monitored by a sensor in some sort of coordinated fashion. Our goal is to develop methodologies by which sites receiving such probes can inferusing purely local observationinformation about the probing activity: What scanning strategies does the probing employ? Is this an attack that specifically targets the site, or is the site only incidentally probed as part of a larger, indiscriminant attack? Our analysis draws upon extensive honeynet data to explore the prevalence of different types of scanning, including properties, such as trend, uniformity, coordination, and darknet avoidance. In addition, we design schemes to extrapolate the global properties of scanning events (e.g., total population and target scope) as inferred from the limited local view of a honeynet. Cross-validating with data from DShield shows that our inferences exhibit promising accuracy.

Original languageEnglish (US)
Article number5599296
Pages (from-to)175-188
Number of pages14
JournalIEEE Transactions on Information Forensics and Security
Volume6
Issue number1
DOIs
StatePublished - Mar 2011

Keywords

  • Botnet
  • computer network security
  • global property extrapolation
  • honeynet
  • scan strategy inference
  • site security monitoring
  • situational awareness
  • statistical inference

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications

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