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ICNS
2007
IEEE
14 years 1 months ago
Data fusion algorithms for network anomaly detection: classification and evaluation
In this paper, the problem of discovering anomalies in a large-scale network based on the data fusion of heterogeneous monitors is considered. We present a classification of anoma...
Vasilis Chatzigiannakis, Georgios Androulidakis, K...
CORR
2010
Springer
206views Education» more  CORR 2010»
13 years 7 months ago
Detecting Anomalous Process Behaviour using Second Generation Artificial Immune Systems
Abstract. Artificial immune systems (AISs) are problem-solving systems inspired by the biological immune system. They have been successfully applied to a number of problem domains ...
Jamie Twycross, Uwe Aickelin, Amanda M. Whitbrook
DSN
2008
IEEE
14 years 2 months ago
Anomaly? application change? or workload change? towards automated detection of application performance anomaly and change
: Automated tools for understanding application behavior and its changes during the application life-cycle are essential for many performance analysis and debugging tasks. Applicat...
Ludmila Cherkasova, Kivanc M. Ozonat, Ningfang Mi,...
IEEEARES
2008
IEEE
14 years 1 months ago
Evaluation of Anomaly Based Character Distribution Models in the Detection of SQL Injection Attacks
The ubiquity of web applications has led to an increased focus on the development of attacks targeting these applications. One particular type of attack that has recently become p...
Mehdi Kiani, Andrew Clark, George M. Mohay
ACSC
2005
IEEE
14 years 1 months ago
Unsupervised Anomaly Detection in Network Intrusion Detection Using Clusters
Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically ...
Kingsly Leung, Christopher Leckie