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Author Viswanathan, R.P. ♦ Al-Nashif, Y. ♦ Hariri, S.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Training ♦ Payloads ♦ Data models ♦ Particle separators ♦ Buffer overflow ♦ Databases ♦ Monitoring ♦ segregation ♦ HTTP ♦ anomaly ♦ framework ♦ multiple models
Abstract Network security, especially application layer security has gained importance with the rapid growth of web-based applications. Anomaly based approaches that profile the network traffic and look for abnormalities are effective against zero-day attacks. The complex nature of the web traffic, availability of multiple applications, privacy concerns and its own limitations make the development of such anomaly-based systems difficult. This paper proposes a framework for application layer anomaly detection. The framework uses a multiple model approach to detect anomalies. The framework encompasses a dedicated training phase to model the specific network traffic and a detection phase that can be deployed in real time. The framework has been applied to HTTP application traffic and multiple models have been developed. The experimental evaluation results of the AADS using multiple attack vectors have achieved a detection rate of almost 100%. In addition, the AADS has a false positive rate of 0.03%.
Description Author affiliation: NSF Center for Autonomic Computing, Department of ECE, University of Arizona, Tucson, Tucson, AZ, U.S.A (Viswanathan, R.P.; Al-Nashif, Y.; Hariri, S.)
ISBN 9781457704758
ISSN 21615330
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-12-27
Publisher Place Egypt
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781457704765
Size (in Bytes) 401.82 kB
Page Count 7
Starting Page 150
Ending Page 156

Source: IEEE Xplore Digital Library