Privacy and integrity-preserving data aggregation scheme for wireless sensor networks digital twins

• Published in: Journal of cloud computing : advances, systems and applications Vol. 12; no. 1; pp. 140 - 11
• Main Authors: Zhang, Zhiming, Yang, Wei, Wu, Fuying, Li, Ping
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2023; Springer Nature B.V; SpringerOpen
• Subjects: Computer Communication Networks; Computer Science; Computer System Implementation; Computer Systems Organization and Communication Networks; Data aggregation; Data integrity; Data management; Digital twins; Edge/Cloud-based Secure; Energy consumption; Fingerprinting; Homomorphic fingerprinting; Information Systems Applications (incl.Internet); Integrity; Network security; Privacy; Privacy function; privacy-conscious digital twins; Sensors; Software Engineering/Programming and Operating Systems; Special Purpose and Application-Based Systems; trustable; Wireless communications; Wireless sensor networks; Data aggregation; Wireless sensor networks; Homomorphic fingerprinting; Digital twins; Privacy function
• ISSN: 2192-113X; 2192-113X
• DOI: 10.1186/s13677-023-00522-7

The security technology of digital twin is an important guarantee to ensure the security of digital twin operation, which mainly includes network security technology, data security technology and privacy protection technology. In wireless sensor networks, data aggregation technologies are known as a suitable solution to reduce energy consumption. In addition, due to wireless communications, wireless sensor networks are subject to many attacks. Therefore, it is very important to provide data security in the data aggregation process. In this paper, in order to protect data privacy and verify data integrity, moreover, balance the energy consumption and security during the data aggregation, we present a privacy and integrity–preserving data aggregation scheme for wireless sensor networks based on digital twins technology and homomorphic fingerprinting (HFPIDA). The HFPIDA adopts privacy function to protect data privacy and adopts homomorphic fingerprinting technology to verify the aggregation data integrity. Security analysis shows that the HFPIDA can effectively preserve data privacy and verify data integrity. Simulation results show that the HFPIDA requires less communication and energy overheads, and can achieve higher aggregation accuracy.