Abstract
Wireless sensor network and big data has gained a lot of importance in recent years. Linear regression, linear classifiers and neural networks have been examined to secure confidential data and enhance privacy protection. The data produced by millions of wireless sensor network generate big data. Big data sources are usually gathered and analysed in wireless sensor network. Therefore major threats prevailing in wireless sensor network must be resolved; hence we proposed an effective hybridized classifier integrated with homomorphic encryption which shows better performances in evaluation. The evaluation shows that the proposed system achieved a higher accuracy rate.
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Udendhran, R., Balamurgan, M. (2020). An Effective Hybridized Classifier Integrated with Homomorphic Encryption to Enhance Big Data Security. In: Haldorai, A., Ramu, A., Mohanram, S., Onn, C. (eds) EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-19562-5_35
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DOI: https://doi.org/10.1007/978-3-030-19562-5_35
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