Achieving Privacy-preserving Data Sharing for Dual Clouds
Author
Abstract

With the advent of the era of Internet of Things (IoT), the increasing data volume leads to storage outsourcing as a new trend for enterprises and individuals. However, data breaches frequently occur, bringing significant challenges to the privacy protection of the outsourced data management system. There is an urgent need for efficient and secure data sharing schemes for the outsourced data management infrastructure, such as the cloud. Therefore, this paper designs a dual-server-based data sharing scheme with data privacy and high efficiency for the cloud, enabling the internal members to exchange their data efficiently and securely. Dual servers guarantee that none of the servers can get complete data independently by adopting secure two-party computation. In our proposed scheme, if the data is destroyed when sending it to the user, the data will not be restored. To prevent the malicious deletion, the data owner adds a random number to verify the identity during the uploading procedure. To ensure data security, the data is transmitted in ciphertext throughout the process by using searchable encryption. Finally, the black-box leakage analysis and theoretical performance evaluation demonstrate that our proposed data sharing scheme provides solid security and high efficiency in practice.

Year of Publication
2022
Conference Name
2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)
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