Technical Reports

A List by Author: Martin Stehlik

e-mail:
xstehl2(a)fi.muni.cz

Towards Better Selective Forwarding And Delay Attacks Detection in Wireless Sensor Networks

by Martin Stehlik, Václav Matyá¹, Andriy Stetsko, A full version of the paper presented at conference ICNSC 2016. April 2016, 30 pages.

FIMU-RS-2016-01. Available as Postscript, PDF.

Abstract:

A number of intrusion detection techniques have been proposed to detect different kinds of active attacks on wireless sensor networks (WSNs). Selective forwarding and delay attacks are two simple but effective attacks that can disrupt the communication in WSNs. In this work, we propose two parametrized collaborative intrusion detection techniques and optimize their parameters for a specific scenario using extensive simulations and multiobjective evolutionary algorithms. Moreover, we sample the whole search space to enable evaluation of evolution performance. The found optimized results are also compared to a simpler non-collaborative detection technique to demonstrate improvements of collaborative approach. We also evaluate the influence of changes of the number of malicious nodes on the intrusion detection performance. This technical report extends our paper presented at conference ICNSC 2016 by details of experiment settings and results.

Improving Intrusion Detection Systems for Wireless Sensor Networks

by Andriy Stetsko, Tobias Smolka, Václav Matyá¹, Martin Stehlik, March 2014, 29 pages.

FIMU-RS-2014-01. Available as Postscript, PDF.

Abstract:

A considerable amount of research has been undertaken in the field of intrusion detection in wireless sensor networks. Researchers proposed a number of relevant mechanisms, and it is not an easy task to select the right ones for a given application scenario. Even when a network operator knows what mechanism to use, it remains an open issue how to configure this particular mechanism in such a way that it is efficient for the particular needs. We propose a framework that optimizes the configuration of an intrusion detection system in terms of detection accuracy and memory usage. There is a variety of scenarios, and a single set of configuration values is not optimal for all of them. Therefore, we believe, such a framework is of a great value for a network operator who needs to optimize an intrusion detection system for his particular needs, e.g., attacker model, environment, node parameters.

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