Community-based Analysis of Netflow for Early Detection of Security Incidents

Research output: Contribution to conferencesPaperContributedpeer-review

Contributors

Abstract

Detection and remediation of security incidents (e.g., attacks, compromised machines, policy violations) is an increasingly important task of system administrators. While numerous tools and techniques are available (e.g., Snort, nmap, netflow), novel attacks and low-grade events may still be hard to detect in a timely manner. In this paper, we present a novel approach for detecting stealthy, low-grade security incidents by utilizing information across a community of organizations (e.g., banking industry, energy generation and distribution industry, governmental organizations in a specific country, etc). The approach uses netflow, a commonly available non-intrusive data source, analyzes communication to/from the community, and alerts the community members when suspicious activity is detected. A community-based detection has the ability to detect incidents that would fall below local detection thresholds while maintaining the number of alerts at a manageable level for each day.

Details

Original languageEnglish
Number of pages20
Publication statusPublished - 2011
Peer-reviewedYes

Conference

Title25th Large Installation System Administration Conference (LISA'11), USENIX Association, 2011
Abbreviated titleUSENIX 2011
Conference number
Duration4 December 2011
Degree of recognitionInternational event
Location
CityBosten
CountryUnited States of America

Keywords

Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards