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Wireless Communications and Mobile Computing
Volume 2017 (2017), Article ID 7623742, 15 pages
Research Article

Performance Comparison of Reputation Assessment Techniques Based on Self-Organizing Maps in Wireless Sensor Networks

1Dipartimento di Scienze Teoriche e Applicate, Università degli Studi dell’Insubria, Via Mazzini 5, 21100 Varese, Italy
2Department of Electrical and Information Engineering, Politecnico di Bari, Via Orabona 4, 70125 Bari, Italy

Correspondence should be addressed to Luigi Alfredo Grieco; ti.abilop@oceirg.oderfla

Received 9 June 2017; Revised 19 September 2017; Accepted 4 October 2017; Published 28 November 2017

Academic Editor: Pierre-Martin Tardif

Copyright © 2017 Sabrina Sicari et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Many solutions based on machine learning techniques have been proposed in literature aimed at detecting and promptly counteracting various kinds of malicious attack (data violation, clone, sybil, neglect, greed, and DoS attacks), which frequently affect Wireless Sensor Networks (WSNs). Besides recognizing the corrupted or violated information, also the attackers should be identified, in order to activate the proper countermeasures for preserving network’s resources and to mitigate their malicious effects. To this end, techniques adopting Self-Organizing Maps (SOM) for intrusion detection in WSN were revealed to represent a valuable and effective solution to the problem. In this paper, the mechanism, namely, Good Network (GoNe), which is based on SOM and is able to assess the reliability of the sensor nodes, is compared with another relevant and similar work existing in literature. Extensive performance simulations, in terms of nodes’ classification, attacks’ identification, data accuracy, energy consumption, and signalling overhead, have been carried out in order to demonstrate the better feasibility and efficiency of the proposed solution in WSN field.