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ISMIS
2005
Springer
15 years 3 months ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni
COMAD
2009
14 years 10 months ago
Categorizing Concepts for Detecting Drifts in Stream
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Sharanjit Kaur, Vasudha Bhatnagar, Sameep Mehta, S...
CCS
2007
ACM
15 years 3 months ago
Non-intrusive IP traceback for DDoS attacks
The paper describes a Non-Intrusive IP traceback scheme which uses sampled traffic under non-attack conditions to build and maintains caches of the valid source addresses transiti...
Vrizlynn L. L. Thing, Morris Sloman, Naranker Dula...
ACSAC
2005
IEEE
15 years 3 months ago
Understanding Complex Network Attack Graphs through Clustered Adjacency Matrices
We apply adjacency matrix clustering to network attack graphs for attack correlation, prediction, and hypothesizing. We self-multiply the clustered adjacency matrices to show atta...
Steven Noel, Sushil Jajodia
VIZSEC
2004
Springer
15 years 2 months ago
Passive visual fingerprinting of network attack tools
This paper examines the dramatic visual fingerprints left by a wide variety of popular network attack tools in order to better understand the specific methodologies used by attack...
Gregory J. Conti, Kulsoom Abdullah