Privacy protection in smart meters using homomorphic encryption: An overview

IF 6.4 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Zita Abreu, Lucas Pereira
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引用次数: 4

Abstract

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.

Abstract Image

使用同态加密的智能电表中的隐私保护:概述
本文概述了智能电表中隐私保护的文献,特别关注同态加密(HE)。首先,我们介绍了智能电表的概念,它们被插入的背景,其使用固有的主要问题和反对意见。随后,对隐私保护进行概述,强调需要通过识别、描述和比较寻求解决这一问题的主要方法来保护智能电表用户的隐私。然后,详细介绍了基于HE的两种隐私保护方法,并提出了两种可能的应用场景。最后,本文简要概述了高等教育尚未解决的挑战和未来最有希望的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
22.70
自引率
2.60%
发文量
39
审稿时长
>12 weeks
期刊介绍: The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD) are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.
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