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Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/143311
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| Title: | Privacy-preserving bidirectional keyword search over encrypted data for cloud-assisted IIoT |
| Authors: | 曾一凡;左瑞麟
Tseng, Yi-Fan;Tso, Raylin
Lee, Cheng-Yi;Liu, Zi-Yuan |
| Contributors: | 資科系 |
| Keywords: | Bidirectional keyword search;IIoT;Pairing-free;Multi-receiver |
| Date: | 2022-09 |
| Issue Date: | 2023-02-06 14:31:27 (UTC+8) |
| Abstract: | Cloud-assisted industrial Internet of Things (IIoT) technology is increasingly used by related enterprises. To preserve the privacy of sensitive data, IIoT devices must encrypt data before sending them to a cloud server. Public-key encryption with keyword search (PEKS) provides an important search function over cloud-assisted IIoT, allowing users to search for encrypted data without decryption. To increase practical functionality, Zhang et al. recently proposed the concept of public-key encryption with bidirectional keyword search, which supports both sender and receiver searches. However, their scheme provides insufficient security because it cannot resist keyword guessing attacks (KGA). Additionally, their scheme requires time-consuming bilinear pairing operations, resulting in high computational costs. In this study, a novel concept called public-key authenticated encryption with bidirectional keyword search was devised for multi-user settings. The system definition and security requirements are formally defined to ensure that no adversary can overcome the indistinguishability against chosen-keyword attacks or KGA. Furthermore, we propose a pairing-free semi-generic construction, combining a multiparty non-interactive protocol and authenticated functionality, which has proven to be secure under the standard model. The experimental results reveal that, compared with other state-of-the-art schemes, the proposed scheme is more practical, secure, and suitable for use with cloud-assisted IIoT systems. |
| Relation: | Journal of Systems Architecture, Vol.130, 102642 |
| Data Type: | article |
| DOI 連結: | https://doi.org/10.1016/j.sysarc.2022.102642 |
| DOI: | 10.1016/j.sysarc.2022.102642 |
| Appears in Collections: | [資訊科學系] 期刊論文
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