Anomaly-based Techniques for Web Attacks Detection

Bruno Augusti Mozzaquatro, Renato Preigschadt de Azevedo, Raul Ceretta Nunes, Alice de Jesus Kozakevicius, Cristian Cappo, Christian Schaerer


The widespread use of the Internet comes accompanied with severe threats for web applications security. Intrusion Detection Systems (IDS) have been considered to deal with the diversity and complexity of web attacks. In this context, this work proposes an algorithm for web attack detection, exploring ananomaly-based technique: the wavelet transform. The proposed algorithm analyzes anomalies within variations on characters frequencies in web requests. Experimental results show high rates of detection without false positive occurrences.

Keywords: Web Attacks, Anomaly Detection, Wavelet Transform, Web Applications.

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This work is licensed under a Creative Commons Attribution 4.0 International License. [updated on August 2016]

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