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Performance evaluation of the impact of attacks on mobile ad hoc networks

: Parsons, Malcolm J.; Ebinger, Peter

Institute of Electrical and Electronics Engineers -IEEE-:
2nd International Workshop on Dependable Network Computing and Mobile Systems, DNCMS 2009. Proceedings : Field Failure Data Analysis; Embedded Systems and Communications Security, in conjunction with 28th IEEE International Symposium on Reliable Distributed Systems, being held in Niagara Falls, New York, U.S.A., September 27-30, 2009
Niagara Falls/NY, 2009
International Workshop on Dependable Network Computing and Mobile Systems (DNCMS) <2, 2009, Niagara Falls/NY>
International Symposium on Reliable Distributed Systems (SRDS) <28, 2009, Niagara Falls/NY>
Fraunhofer IGD ()
mobile ad-hoc networks (MANETs); network security; performance evaluation; attack mechanism; performance metric

The rise in research on and use of Mobile Ad hoc Networks (MANETs) has seen an equal increase in the number of attack strategies, detection methods and counter measures proposed. Most of these have been analyzed and evaluated in separate simulation experiments according to performance metrics chosen for a specific purpose, however, simulation results are not comparable due to varying evaluation scenarios and implementations.
In this paper we implement and evaluate the most prominent attacks described in literature in a consistent manner to provide a concise comparison on attack types and parameters. Our objective is to thoroughly capture and analyze the impact of a range of attacks on MANET performance. To this end we define performance metrics and explore influence and damage caused by several attack types and parameter sets.
Our evaluation results show that the degree of impact of attacks differs significantly depending on attack type and parameters used. The impact of a particular attack increases considerably with an increasing number of attacking nodes in several of the scenarios, whereas other attack impact levels remain almost constant with varying number of attackers. These results imply that an attacker could choose an attack strategy from a number of alternatives with similar overall impact thereby minimizing detection risk. Our performance metrics provide a consistent comparison of various attack types and parameters and thus a deeper insight into the interaction and the impact of attacks in MANETs.