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As a major breakthrough, in 2009 Gentry introduced the first plausible construction of a fully homomorphic encryption (FHE) scheme. FHE allows the evaluation of arbitrary functions directly on encrypted data on untwisted servers. In 2010, Gentry and Halevi presented the first FHE implementation on an IBM x3500 server. However, this implementation remains(More)
—In 2010 Gentry and Halevi presented the first FHE implementation. FHE allows the evaluation of arbitrary functions directly on encrypted data on untrusted servers. However, even for the small setting with 2,048 dimensions, the authors reported a performance of 1.8 seconds for a single bit encryption and 32 seconds for recryption on a high end server. Much(More)
This paper presents the design of a powerand areaefficient high-speed 768 000-bit multiplier, based on fast Fourier transform multiplication for fully homomorphic encryption operations. A memory-based in-place architecture is presented for the FFT processor that performs 64 000-point finite-field FFT operations using a radix-16 computing unit and 16(More)
Modular multiplication is the most crucial component in RSA cryptosystem. In this paper, we present a new modular multiplication architecture using the Strassen multiplication algorithm and Montgomery reduction. The architecture is different from the interleaved version of Montgomery multiplication traditionally used in RSA design. By selecting different(More)
Hearing Loss is one of the three most common chronic conditions among the elderly. In many cases, an individuals hearing is only impaired at certain (not all) frequencies. Analog hearing aids boost all sound frequencies equally including frequencies in which the individuals hearing is good, causing discomfort to the user. Digital hearing aids can amplify(More)
In recent years, deep learning has attracted lots of research interests for pattern recognition and artificial intelligence. PCA Network (PCANet) is a simple deep learning network with highly competitive performance for texture classification and object recognition. When compared to other deep neural networks such as convolutional neural network (CNN),(More)