A remote sensing encrypted data search method based on a novel double-chain. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Yan, Xixi; Yin, Pei; Tang, Yongli; Feng, Suwei
• Is Part Of: Connection science. Volume 35:Issue 1(2023)
• Publication Date: 2023-12-31
• Subjects: Searchable encryption -- remote sensing data -- forward security -- smart cities -- privacy protection; TP309; Neural computers -- Periodicals; Artificial intelligence -- Periodicals; Cognitive science -- Periodicals; Connectionism -- Periodicals; 006.3
• DOI: 10.1080/09540091.2023.2165638
• Languages: English
• ISSNs: 0954-0091

Abstract

Abstract : Remote sensing is considered to be a key technology for the development of smart cities. By analysing the data obtained by remote sensing, it is effective to manage and develop smart cities. However, with the rapid urbanisation and the increase in data capacity, how to store and retrieve remote sensing data which have more potential value and privacy with a more effective and safe method has become an imminent issue. In this paper, we propose an efficient verifiable and dynamic multi-keyword searchable encryption scheme for remote sensing data in smart cities. Moreover, we construct a double-chain index to support a multi-keyword search, where the Verification Index Chain is used to identify the users and the Keyword Index Chain is used to store the information of keywords. In addition, we adopt extended bitmap technology to realise update operations and verify the correctness and integrity of the search results. Experiments show that compared to the related existing schemes, the search time of the proposed scheme is reduced by 35% at most, the verification time is reduced by 14% at most and the update time is reduced by 57% at most.