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Extra info for Adaptive real-time anomaly detection for safeguarding critical networks
In parallel the hybrid detector agent increases coverage by providing additional types of alerts. The processing of the hybrid detection agents and correlation agents are further described in the following sections. 2 Hybrid detector agent The hybrid detector agent combines learning-based anomaly detection with programming–based detection using signatures. 3. T HE S AFEGUARD AGENTS detect and categorise known problems, while the anomaly detection engine can detect new unknown attacks and problems.
2 Hybrid detector agent The hybrid detector agent combines learning-based anomaly detection with programming–based detection using signatures. 3. T HE S AFEGUARD AGENTS detect and categorise known problems, while the anomaly detection engine can detect new unknown attacks and problems. In the telecom domain the data rate can be very high, compared to the electricity domain. This puts hard requirements in terms of performance and scalability of the hybrid detector agent. ADWICE, the anomaly detection scheme presented in the next chapters of this thesis, as well as a separate instance of the hybrid detector agent, was implemented to fulfil those needs.
5: Misuse detection versus anomaly detection Intrusion detection depends on the assumption that the data source has access to data where attacks are different from normal data. Moreover, this difference needs to be captured by the events produced by the sensor and by the model of the analyser to correctly produce alerts when attacks are present in the data. Two common approaches exist: • Misuse detection, also known as Knowledge-based intrusion detection, which uses an internal model of attacks (misuse) to detect intrusions.