Discovering collaborative cyber attack patterns using social network analysis
- Haitao Du(corresponding author),
- Rochester Institute of Technology
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Abstract
This paper investigates collaborative cyber attacks based on social network analysis. An Attack Social Graph (ASG) is defined to represent cyber attacks on the Internet. Features are extracted from ASGs to analyze collaborative patterns. We use principle component analysis to reduce the feature space, and hierarchical clustering to group attack sources that exhibit similar behavior. Experiments with real world data illustrate that our framework can effectively reduce from large dataset to clusters of attack sources exhibiting critical collaborative patterns.
Bibliographic Information
Output type
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Original language
EnglishPages from-to (Number of pages)
Pages 129-136 (8 pages)Publication milestones
- Published - 2011
Publication status
Published - 2011
Publication series
- Publication series name: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print): 0302-9743
ISSN (Electronic): 1611-3349
Volume: 6589 LNCS
ISBN (Print)
9783642196553Publication IDs
- Scopus: 79952396643
