PPCT: Privacy-Preserving Contact Tracing Using Concise Private Set Intersection Cardinality

• Published in: Journal of network and systems management 2024-10, Vol.32 (4), p.97, Article 97
• Main Authors: Yang, Qianheng, Yang, Yuer, Xu, Shiyuan, Guo, Rongrong, Xian, Huiguang, Lin, Yifeng, Chen, Xue, Tan, Wuzheng, Yiu, Siu-Ming
• Format: Article
• Language: English
• Subjects: Communications Engineering; Computed tomography; Computer Communication Networks; Computer Science; Computer Systems Organization and Communication Networks; Computing costs; Contact tracing; Infectious diseases; Information Systems and Communication Service; Networks; Operations Research/Decision Theory; Personal information; Privacy
• ISSN: 1064-7570; 1573-7705
• DOI: 10.1007/s10922-024-09865-1

Contact tracing (CT) is an indispensable tool in controlling infectious disease outbreaks, which is regarded as the most effective weapon for curbing the spread of viruses. Due to the emergence of infectious diseases, many countries have implemented CT systems to mitigate the spread of the virus. Nevertheless, existing systems are either insufficiently secure or have high computational requirements for resource-constrained client devices. Thus, in this paper, we propose PPCT, an efficient and privacy-preserving CT system that prevents all significant attacks present in most CT systems. Our system ensures that the personal information of diagnosed users remains private from both the server and other users. Specifically, by employing our new and concise private set intersection cardinality (CPSI-CA) protocol, PPCT can efficiently answer user queries while preserving the privacy of personal information and query results. Furthermore, we conducted extensive experiments, and the results show that PPCT outperforms most existing systems in terms of computational cost and communication overhead, which demonstrates the feasibility of PPCT. More specifically, our scheme has improved a hundred times on client runtime.