Privacy-Preserving Protocols for Eigenvector Computation - Computer Science > Cryptography and SecurityReport as inadecuate




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Abstract: In this paper, we present a protocol for computing the principal eigenvectorof a collection of data matrices belonging to multiple semi-honest parties withprivacy constraints. Our proposed protocol is based on secure multi-partycomputation with a semi-honest arbitrator who deals with data encrypted by theother parties using an additive homomorphic cryptosystem. We augment theprotocol with randomization and obfuscation to make it difficult for any partyto estimate properties of the data belonging to other parties from theintermediate steps. The previous approaches towards this problem were based onexpensive QR decomposition of correlation matrices, we present an efficientalgorithm using the power iteration method. We analyze the protocol forcorrectness, security, and efficiency.



Author: Manas A. Pathak, Bhiksha Raj

Source: https://arxiv.org/







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