Secure Localization Techniques in Wireless Sensor Networks Against Routing Attacks Using Machine Learning Models
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-8669-7_52
Reference20 articles.
1. Robinson, Y.H., Golden, S.V.E., Lakshmi, J.K.: 3—Dimensional Manifold and Machine Learning Based Localization Algorithm for Wireless Sensor Networks. Wirel. Pers. Commun. (0123456789) (2021). https://doi.org/10.1007/s11277-021-08291-9
2. Chen, J., Zhang, W., Liu, Z., Wang, R., Zhang, S.: CWDV-hop: a hybrid localization algorithm with distance-weight DV-Hop and CSO for wireless sensor networks. IEEE Access 9, 380–399 (2021). https://doi.org/10.1109/ACCESS.2020.3045555
3. Giri, A., Dutta, S., Neogy, S.: Information-theoretic approach for secure localization against sybil attack in wireless sensor network. J. Ambient Intell. Humaniz. Comput. (0123456789) (2020). https://doi.org/10.1007/s12652-020-02690-9
4. Singh, M.M., Dutta, N., Singh, T.R., Nandi, U.: A technique to detect wormhole attack in wireless sensor network using artificial neural network, vol. 53. Springer, Singapore (2021). https://doi.org/10.1007/978-981-15-5258-8_29
5. Chen, H., Lou, W., Wang, Z., Wu, J., Wang, Z., Xi, A.: Securing DV-Hop localization against wormhole attacks in wireless sensor networks. Pervasive Mob. Comput. 16(PA), 22–35 (2015). https://doi.org/10.1016/j.pmcj.2014.01.007
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