IDAMN: an intrusion detection architecture for mobile networks

Abstract

-In this paper we present IDAMN, a distributed system whose main functionality is to track and detect mobile intruders in real-time. IDAMN includes two algorithms which model the behaviour of users in terms of both telephony activity and migration pattern. The main novelty of our architecture is its ability to perform intrusion detection in the visited location and within the duration of a typical call as opposed to existing designs that require the reporting of all call data to the home location in order to perform the actual detection. The algorithms and the components of IDAMN have been designed in order to minimize the overhead incurred in the fixed part of the cellular network.

Behaviour Profiling on Mobile Devices

“…Any deviation between the current calling session and the historical profile that exceeds a threshold, is identified as an intrusion. Several studies were proposed by using this procedure, such as the European ASPECT (Advanced Security for Personal Communication Technologies) project [5], [6], and [7].…”

Cloud based intrusion detection architecture for smartphones

“…Finally, they came up with a unified intrusion detection model. Samfat and Molva [5] propose architecture for mobile networks -IDAMN and they use anomaly detection methods as well as rule-based methods. There are three levels of detection; Location based detection (user located at two different locations at the same time), traffic anomaly detection (extremely low or extremely high levels network traffic), and the detection of anomalous behavior of specific mobile phone user.…”

Data Mining For Intrusion Detection in Mobile Systems

“…IDAMN: Samfat et.al [3] 1997 proposed Intrusion detection architecture for mobile networks. Their systems main functionality is its ability to perform intrusion detection in the visited location and within the duration of a typical call.…”