Prevention and Fighting against Web Attacks through Anomaly Detection Technology. A Systematic Review

Numerous techniques have been developed in order to prevent attacks on web servers. Anomaly detection techniques are based on models of normal user and application behavior, interpreting deviations from the established pattern as indications of malicious activity. In this work, a systematic review o...

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Bibliographic Details
Published in:Sustainability 2020-06, Vol.12 (12), p.4945
Main Authors: Sureda Riera, Tomás, Bermejo Higuera, Juan-Ramón, Bermejo Higuera, Javier, Martínez Herraiz, José-Javier, Sicilia Montalvo, Juan-Antonio
Format: Article
Language:English
Subjects:
Anomalies
Cloud computing
Datasets
Deep learning
International organizations
Intrusion detection systems
Literature reviews
Methods
Prevention
Reviews
Statistical analysis
Studies
Sustainability
Systematic review
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Summary:Numerous techniques have been developed in order to prevent attacks on web servers. Anomaly detection techniques are based on models of normal user and application behavior, interpreting deviations from the established pattern as indications of malicious activity. In this work, a systematic review of the use of anomaly detection techniques in the prevention and detection of web attacks is undertaken; in particular, we used the standardized method of a systematic review of literature in the field of computer science, proposed by Kitchenham. This method is applied to a set of 88 papers extracted from a total of 8041 reviewed papers, which have been published in notable journals. This paper discusses the process carried out in this systematic review, as well as the results and findings obtained to identify the current state of the art of web anomaly detection.
ISSN:2071-1050
2071-1050
DOI:10.3390/su12124945