Abstract:Fully Homomorphic Encryption (FHE) is one of the most promising technologies for privacy protection as it allows an arbitrary number of function computations over encrypted data. However, the computational cost of these FHE systems limits their widespread applications. In this paper, our objective is to improve the performance of FHE schemes by designing efficient parallel frameworks. In particular, we choose Torus Fully Homomorphic Encryption (TFHE) [1] as it offers exact results for an infinite number of boo… Show more
“…However, one of the major problems of HE is the high computational cost of performing operations on top of encrypted data that are several orders of magnitude slower than operations on unencrypted data. 1 Against this background, recent times have seems some efforts toward improving the computational performance of HE by introducing hardware acceleration using GPU, FPGA, and possibly ASICs, for example, (Morshed et al, 2020;Roy et al, 2017;Yang et al, 2020). Furthermore, some efforts have also been developed toward producing custom hardware for HE.…”
This article presents an overview of the literature on privacy protection in smart meters with a particular focus on homomorphic encryption (HE).Firstly, we introduce the concept of smart meters, the context in which they are inserted the main concerns and oppositions inherent to its use. Later, an overview of privacy protection is presented, emphasizing the need to safeguard the privacy of smart-meter users by identifying, describing, and comparing the main approaches that seek to address this problem. Then, two privacy protection approaches based on HE are presented in more detail and additionally we present two possible application scenarios. Finally, the article concludes with a brief overview of the unsolved challenges in HE and the most promising future research directions.
“…However, one of the major problems of HE is the high computational cost of performing operations on top of encrypted data that are several orders of magnitude slower than operations on unencrypted data. 1 Against this background, recent times have seems some efforts toward improving the computational performance of HE by introducing hardware acceleration using GPU, FPGA, and possibly ASICs, for example, (Morshed et al, 2020;Roy et al, 2017;Yang et al, 2020). Furthermore, some efforts have also been developed toward producing custom hardware for HE.…”
This article presents an overview of the literature on privacy protection in smart meters with a particular focus on homomorphic encryption (HE).Firstly, we introduce the concept of smart meters, the context in which they are inserted the main concerns and oppositions inherent to its use. Later, an overview of privacy protection is presented, emphasizing the need to safeguard the privacy of smart-meter users by identifying, describing, and comparing the main approaches that seek to address this problem. Then, two privacy protection approaches based on HE are presented in more detail and additionally we present two possible application scenarios. Finally, the article concludes with a brief overview of the unsolved challenges in HE and the most promising future research directions.
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