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|Title:||FS-PEKS : lattice-based forward secure public-key encryption with keyword search for cloud-assisted Industrial Internet of Things||Authors:||Zhang, Xiaojun
|Keywords:||Science::Mathematics||Issue Date:||2021||Source:||Zhang, X., Xu, C., Wang, H., Zhang, Y. & Wang, S. (2021). FS-PEKS : lattice-based forward secure public-key encryption with keyword search for cloud-assisted Industrial Internet of Things. IEEE Transactions On Dependable and Secure Computing, 1019(1032), 18-3. https://dx.doi.org/10.1109/TDSC.2019.2914117||Journal:||IEEE Transactions on Dependable and Secure Computing||Abstract:||Cloud-assisted Industrial Internet of Things (IIoT) relies on cloud computing to provide massive data storage services. To ensure the confidentiality, sensitive industrial data need to be encrypted before being outsourced to cloud storage server. Public-key encryption with keyword search (PEKS) enables users to search target encrypted data by keywords. However, most existing PEKS schemes are based on conventional hardness assumptions, which are vulnerable to adversaries equipped with quantum computers in the near future. Moreover, they suffer from key exposure, and thus the security would be broken once the keys are compromised. In this paper, we propose a forward secure PEKS scheme (FS-PEKS) based on lattice assumptions for cloud-assisted IIoT, which is post-quantum secure. We integrate a lattice-based delegation mechanism into FS-PEKS to achieve forward security, such that the security of the system is still guaranteed even the keys are compromised by the adversaries. We define the first formal security model on forward security of PEKS, and prove the security of FS-PEKS under the model. As the keywords of industrial data are with inherently low entropy, we further extend FS-PEKS to resist insider keyword guessing attacks (IKGA). The comprehensive performance evaluation demonstrates that FS-PEKS is practical for cloud-assisted IIoT.||URI:||https://hdl.handle.net/10356/151970||ISSN:||1545-5971||DOI:||10.1109/TDSC.2019.2914117||Rights:||© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TDSC.2019.2914117||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SPMS Journal Articles|
Updated on Jul 4, 2022
Updated on Jul 4, 2022
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