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Towards fuzzy anomaly detection-based security: a comprehensive review
Ist Teil von
Fuzzy optimization and decision making, 2021-03, Vol.20 (1), p.1-49
Ort / Verlag
New York: Springer US
Erscheinungsjahr
2021
Link zum Volltext
Quelle
Business Source Ultimate
Beschreibungen/Notizen
In the data security context, anomaly detection is a branch of intrusion detection that can detect emerging intrusions and security attacks. A number of anomaly detection systems (ADSs) have been proposed in the literature that using various algorithms and techniques try to detect the intrusions and anomalies. This paper focuses on the ADS schemes which have applied fuzzy logic in combination with other machine learning and data mining techniques to deal with the inherent uncertainty in the intrusion detection process. For this purpose, it first presents the key knowledge about intrusion detection systems and then classifies the fuzzy ADS approaches regarding their utilized fuzzy algorithm. Afterward, it summarizes their major contributions and illuminates their advantages and limitations. Finally, concluding issues and directions for future researches in the fuzzy ADS context are highlighted.