Abstract
k-Means is a widely used clustering algorithm that divides data points into k groups. Previous studies focus on implementing secure k-Means clustering either for single user or for multiple users. The common way is to operate on outsourced and encrypted datasets in the cloud. Two difficulties exist in this procedure - how to handle with different keys and how to compute distance, comparison and division on the ciphertexts. On the other hand, k-Means algorithm includes many unnecessary distance calculations. In this paper, we aim to construct privacy-preserving protocol which accelerates k-Means algorithm for data encrypted by different keys in the cloud. Experiments show that our scheme is effective.
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Zhang, J., Wang, Y., Li, B., Hu, S. (2021). Privacy-Preserving Accelerated Clustering for Data Encrypted by Different Keys. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2020. Lecture Notes in Computer Science(), vol 12608. Springer, Cham. https://doi.org/10.1007/978-3-030-74717-6_17
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DOI: https://doi.org/10.1007/978-3-030-74717-6_17
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