Privacy-Preserving Single Layer Perceptron
Publish place: 6th Iranian Security Community Conference
Publish Year: 1388
Type: Conference paper
Language: English
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ISCC06_006
Index date: 7 July 2010
Privacy-Preserving Single Layer Perceptron abstract
In this paper, we will introduce several notions of privacy, such as k-anonymity, p-indistinguishability, (c,t)-isolation, and SMC-based measures. We then turn our attention to privacy-preserving classification algorithms. We propose two approaches to classify data using a neural-network classifier called perceptron. The first approach is based on probabilistic encryption, while the second one is based on simple random computations. The two approaches are then compared, and the advantages and disadvantages of each are considered.
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Privacy-Preserving Single Layer Perceptron authors
Mohammad Sadeq Dousti۱
Network Security Center, Department of Computer Engineering
Maryam AmirHaeri۱
Network Security Center, Department of Computer Engineering
Rassol Jalili۱
Network Security Center, Department of Computer Engineering
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