Anomaly-based Techniques for Web Attacks Detection | Zendy

Bruno A. Mozzaquatro | Zendy; Renato Preigschadt de Azevedo | Zendy; Raul Ceretta Nunes | Zendy; Alice Kozakevicius | Zendy; Cristian Cappo | Zendy; Christian E. Schaerer | Zendy

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Anomaly-based Techniques for Web Attacks Detection

Author(s) -

Bruno A. Mozzaquatro,

Renato Preigschadt de Azevedo,

Raul Ceretta Nunes,

Alice Kozakevicius,

Cristian Cappo,

Christian E. Schaerer

Publication year - 2012

Publication title -

journal of applied computing research

Language(s) - English

Resource type - Journals

ISSN - 2236-8434

DOI - 10.4013/jacr.2011.12.06

Subject(s) - intrusion detection system , computer science , context (archaeology) , anomaly detection , the internet , web application security , internet security , wavelet , web application , web analytics , data mining , wavelet transform , computer security , world wide web , web development , artificial intelligence , information security , geology , security service , paleontology

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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