Abstract
We present a new approach to anomaly-based network intrusion detection for web applications. This approach is based on dividing the input parameters of the monitored web application in two groups: the “regular” and the “irregular” ones, and applying a new method for anomaly detection on the “regular” ones based on the inference of a regular language. We support our proposal by realizing Sphinx, an anomaly-based intrusion detection system based on it. Thorough benchmarks show that Sphinx performs better than current state-of-the-art systems, both in terms of false positives/false negatives as well as needing a shorter training period.
This research is supported by the research program Sentinels (http://www.sen tinels.nl). Sentinels is being financed by Technology Foundation STW, the Netherlands Organization for Scientific Research (NWO), and the Dutch Ministry of Economic Affairs.
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Bolzoni, D., Etalle, S. (2008). Boosting Web Intrusion Detection Systems by Inferring Positive Signatures . In: Meersman, R., Tari, Z. (eds) On the Move to Meaningful Internet Systems: OTM 2008. OTM 2008. Lecture Notes in Computer Science, vol 5332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88873-4_2
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DOI: https://doi.org/10.1007/978-3-540-88873-4_2
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