Abstract
This paper presents WebIDS, a learning-based anomaly detection system for Web applications aiming at improving the decision process, reducing the number of false positives, and achieving distributed detection.
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Debar, H., Curry, D., Feinstein, B.: The Intrusion Detection Message Exchange Format. Internet Draft IETF (2005), http://www.ietf.org/internet-drafts/draft-ietf-idwg-idmef-xml-14.txt
Julisch, K.: Using Root Cause Analysis to Handle Intrusion Detection Alarms. PhD Thesis, University of Dortmund, Germany (2003)
Kruegel, C., Mutz, D., Robertson, W., Valeur, F.: Bayesian Event Classification for Intrusion Detection. In: 19th Annual Computer Security Applications Conference. IEEE Computer Society Press, New York (2003)
Kruegel, C., Valeur, F., Vigna, G.: Intrusion Detection and Correlation - Challenges and Solutions. In: Advances in Information Security, vol. 14. Springer, Heidelberg (2005)
Kruegel, C., Vigna, G., Robertson, W.: A Multi-Model Approach to the Detection of Web-Based Attacks. Computer Networks 48(5), 717–738 (2005)
Valdes, A., Skinner, K.: Adaptive, Model-Based Monitoring for Cyber Attack Detection. In: 3rd International Symposium on Recent Advances in Intrusion Detection, pp. 80–92. Springer, Heidelberg (2000)
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Dagorn, N. (2008). WebIDS: A Cooperative Bayesian Anomaly-Based Intrusion Detection System for Web Applications (Extended Abstract). In: Lippmann, R., Kirda, E., Trachtenberg, A. (eds) Recent Advances in Intrusion Detection. RAID 2008. Lecture Notes in Computer Science, vol 5230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87403-4_22
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DOI: https://doi.org/10.1007/978-3-540-87403-4_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87402-7
Online ISBN: 978-3-540-87403-4
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