DoS detection in WSNs: Energy-efficient designs and modeling tools for choosing monitoring nodes

Abstract : The use of wireless sensor networks (WSNs) has increased rapidly over the last years. Due to their low resources, sensors come along with new issues regarding network security and energy consumption. Focusing on the network availability, previous studies proposed to protect clustered network against denial of service attacks with the use of traffic monitoring agents on some nodes. Those control nodes have to analyze the traffic inside a cluster and to send warnings to the cluster-head whenever an abnormal behavior (i.e., high packets throughput) is detected. But if the control nodes (cNodes) die out of exhaustion, they leave the network unprotected. To better fight against attacks, we try to enhance this solution by renewing periodically the election process. Furthermore, we propose two energy-aware and secure methods to designate the cNodes in a hierarchically clustered WSN. The first one is a self-election process where nodes randomly designate themselves. We analyze the trade-offs between static and dynamic solutions by means of two complementary approaches: through simulation with the ns-2 simulation platform and by means of statistical model checking with the Hybrid Automata Stochastic Logic. The second algorithm for choosing cNodes is purely based on the residual energy of the sensors. We discuss limitations of this deterministic process concerning security and cluster coverage, and suggest workarounds. Again, experimental results from simulation experiments are provided to analyse the energy repartition in the network. All experimental outcomes show improvements of the load balancing in the network, while maintaining good detection coverage.
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Submitted on : Thursday, May 19, 2016 - 7:45:34 PM
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Quentin Monnet, Lynda Mokdad. DoS detection in WSNs: Energy-efficient designs and modeling tools for choosing monitoring nodes . Mohammad S. Obaidat; Faouzi Zaraia; Petros Nicopolitidis. Modeling and Simulation of Computer Networks and Systems: Methodologies and Applications, Elsevier, pp.797−842, 2015, 9780128008874. ⟨http://store.elsevier.com/Modeling-and-Simulation-of-Computer-Networks-and-Systems/isbn-9780128008874/⟩. ⟨hal-01318714⟩

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