Abstract
In this paper, we propose an efficient approach for privacy preserving distributed k-means clustering in unsecured horizontally distributed data. We use an elliptic curve cryptography to offer data privacy and security against involving sites and an external adversary. We analyze the proposed approach in terms of privacy, security, communication, and computational cost.
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Shewale, A., Keshavamurthy, B.N., Modi, C.N. (2019). An Efficient Approach for Privacy Preserving Distributed K-Means Clustering in Unsecured Environment. In: Sa, P., Bakshi, S., Hatzilygeroudis, I., Sahoo, M. (eds) Recent Findings in Intelligent Computing Techniques . Advances in Intelligent Systems and Computing, vol 707. Springer, Singapore. https://doi.org/10.1007/978-981-10-8639-7_44
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DOI: https://doi.org/10.1007/978-981-10-8639-7_44
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