An Efficient Searchable Symmetric Encryption Scheme for Smart Grid Data

Abstract

In recent years, the combination of power systems and IoT (Internet of things) has become a new generation of smart grid. Cloud computing is used to provide storage and computing services for smart grid data due to its convenience. Generally, searchable encryption technology is considered a feasible solution to guarantee data security and support search function. Li proposed a searchable symmetric encryption scheme based on pseudo-random function for smart grid data in 2019. In this paper, we propose a more efficient and more secure searchable symmetric encryption scheme for smart grid data. The scheme improves the search efficiency by introducing the Bloom filter and changing the structure of the index. Specifically, we first narrow the search scope and then perform a second search, which eliminates the false positive caused by the introduction of the Bloom filter. At the same time, we assign an ID to each piece of data (a row of data) in a tabular dataset, store the hash value of the ID (adding salt) in the index, and the search results are returned by the server contain none of the ID information, which improves security. Experiments on real data show that our scheme is 52% more efficient than the previous scheme.

Towards Efficient Federated Learning Using Agile Aggregation in Internet of Vehicles

“…Te efcient model training issue has been investigated while protecting data privacy in the scenario of high-dynamic data in IoV. Xiong et al in [46,47] proposed a vehicle crowdsensing system based on blockchain and a privacy protection method by IoV sensing. Cha et al in [48] proposed a client selection scheme based on fuzzy logic.…”