scholarly journals Detecting and Confining Sybil Attack in Wireless Sensor Networks Based on Reputation Systems Coupled with Self-organizing Maps

2010 ◽  
pp. 311-318 ◽  
Author(s):  
Zorana Banković ◽  
David Fraga ◽  
José M. Moya ◽  
Juan Carlos Vallejo ◽  
Álvaro Araujo ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Reputation Systems ◽  
Sybil Attack ◽  
Self Organizing Maps ◽  
Self Organizing

scholarly journals A new QoS routing algorithm based on self-organizing maps for wireless sensor networks

2007 ◽  
Vol 36 (1-3) ◽  
pp. 73-83 ◽  
Author(s):  
Julio Barbancho ◽  
Carlos León ◽  
F. Javier Molina ◽  
Antonio Barbancho
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Algorithm ◽  
Qos Routing ◽  
Wireless Sensor ◽  
Self Organizing Maps ◽  
Qos Routing Algorithm ◽  
Self Organizing

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

2017 ◽  
Vol 2017 ◽  
pp. 1-15
Author(s):  
Sabrina Sicari ◽  
Alessandra Rizzardi ◽  
Luigi Alfredo Grieco ◽  
Alberto Coen-Porisini
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Comparison ◽  
Sensor Nodes ◽  
Machine Learning Techniques ◽  
Wireless Sensor ◽  
Dos Attacks ◽  
Self Organizing Maps ◽  
Similar Work ◽  
Self Organizing

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.

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