Please use this identifier to cite or link to this item:
Title: FS-PEKS : lattice-based forward secure public-key encryption with keyword search for cloud-assisted Industrial Internet of Things
Authors: Zhang, Xiaojun
Xu, Chunxiang
Wang, Huaxiong
Zhang, Yuan
Wang, Shixiong
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.
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.
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:
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

Files in This Item:
File Description SizeFormat 
FS-PEKS .pdf1.78 MBAdobe PDFView/Open

Page view(s)

Updated on Jul 4, 2022

Download(s) 20

Updated on Jul 4, 2022

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.