Cross-layer Analysis for Detecting Wireless Misbehavior

Start: Wednesday, October 19, 2005, 10:30AM

End: Wednesday, October 19, 2005, 12:00PM

Location: ITE 325

Abstract: Intrusion Detections Systems(IDSs) in ad hoc networks monitor other devices for intentional deviation from protocol, i.e., misbehavior. This process is complicated due to limited radio range and mobility of nodes. Unlike conventional IDSs, it is not possible to monitor nodes for long durations. As a result IDSs suffer from a large number of false positives. Moreover other environmental conditions like radio interference and congestion increase false positives, complicating classification of legitimate nodes and attackers.

We present a scheme that helps in accurate diagnosis of malicious attacks in ad hoc networks. Our scheme employs cross-layer interactions based on observations at various networking layers to decrease the number of false positives. Our simulations show that our scheme is more effective and accurate than those based on isolated observations from any single layer.

Tags: cross-layer analysis, intrusion detection, manet

Part of:

eBiquity meeting Fall 2005

Assertions:

(Event) Cross-layer Analysis for Detecting Wireless Misbehavior has (Resource) Cross-layer Analysis for Detecting Wireless Misbehavior. (Cross layer analysis for IDS slides, presented in eBiquity meeting 20 Oct., 2005)


	UMBC eBiquity Events / Talks Cross-layer Analysis for Detecting Wireless Misbehavior OWL metadata Update record		Cross-layer Analysis for Detecting Wireless Misbehavior Tweet Speaker: Anand Patwardhan Start: Wednesday, October 19, 2005, 10:30AM End: Wednesday, October 19, 2005, 12:00PM Location: ITE 325 Abstract: Intrusion Detections Systems(IDSs) in ad hoc networks monitor other devices for intentional deviation from protocol, i.e., misbehavior. This process is complicated due to limited radio range and mobility of nodes. Unlike conventional IDSs, it is not possible to monitor nodes for long durations. As a result IDSs suffer from a large number of false positives. Moreover other environmental conditions like radio interference and congestion increase false positives, complicating classification of legitimate nodes and attackers. We present a scheme that helps in accurate diagnosis of malicious attacks in ad hoc networks. Our scheme employs cross-layer interactions based on observations at various networking layers to decrease the number of false positives. Our simulations show that our scheme is more effective and accurate than those based on isolated observations from any single layer. Tags: cross-layer analysis, intrusion detection, manet Part of: eBiquity meeting Fall 2005 Assertions: (Event) Cross-layer Analysis for Detecting Wireless Misbehavior has (Resource) Cross-layer Analysis for Detecting Wireless Misbehavior. (Cross layer analysis for IDS slides, presented in eBiquity meeting 20 Oct., 2005) ,