An efficient voting based method to detect sink hole in wireless acoustic sensor networks

Author:

Nithiyanandam N.,Parthiban Latha

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Reference13 articles.

1. Chen, C., Song, M., & Hsieh, G. (2010). Intrusion detection of sinkhole attacks in large-scale wireless sensor networks. In IEEE international conference on wireless communications, networking and information security (WCNIS) (pp. 711–716). IEEE.

2. Cobos, M., Antonacci, F., Alexandridis, A., Mouchtaris, A., & Lee, B. (2017). A survey of sound source localization methods in wireless acoustic sensor networks. Wireless Communications and Mobile Computing. https://doi.org/10.1155/2017/3956282.

3. Dallas, D., Leckie, C., & K. Ramamohanarao. (2007). Hop-count monitoring: Detecting sinkhole attacks in wireless sensor networks. In 15th IEEE international conference on networks, 2007. ICON 2007 (pp. 176–181). IEEE.

4. Ibrahim, A., Rahman, M. M., & Chandra Roy, M. (2015). Detecting sinkhole attacks in wireless sensor network using hop count. International Journal of Computer Network and Information Security,7(3), 50.

5. Jiang, H. F., & Xu, Y. (2011). Research advances on security problems of underwater sensor networks. In X. Chen (Ed.), Advanced materials research (pp. 1002–1006). Portico: Trans Tech Publications Ltd.

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