Towards a Compressive-Sensing-Based Lightweight Encryption Scheme for the Internet of Things

Xue, Wanli and Luo, Chengwen and Shen, Yiran and Rana, Rajib ORCID: https://orcid.org/0000-0002-0506-2409 and Lan, Guohao and Jha, Sanjay and Seneviratne, Aruna and Hu, Wen (2021) Towards a Compressive-Sensing-Based Lightweight Encryption Scheme for the Internet of Things. IEEE Transactions on Mobile Computing, 20 (10). pp. 3049-3065. ISSN 1536-1233


Abstract

Internet of Things (IoT) is flourishing and has penetrated deeply into people’s daily life. With the seamless connection to the physical world, IoT provides tremendous opportunities to a wide range of applications. However, potential risks exist when the IoT system collects sensor data and uploads it to the Cloud. The leakage of private data can be severe with curious database administrator or malicious hackers who compromise the Cloud. In this work, we propose Kryptein, a compressive-sensing-based lightweight encryption scheme for Cloud-enabled IoT systems to secure the interaction between the IoT devices and the Cloud. Kryptein supports random compressed encryption, statistical computation over cipher, and accurate raw data decryption. According to our evaluation based on two real datasets, Kryptein provides strong protection to the data. It is 250 times faster than other state-of-the-art systems and incurs 120 times less energy consumption. The performance of Kryptein is also measured on off-the-shelf IoT devices, and the result shows Kryptein can run efficiently on IoT devices. After comparing with other state-of-the-art lightweight ciphers on IoT (Simon and Speck), IoT system with Kryptein is expected to have a much more longevity with about 35 percent extended lifetime. Further, experiments illustrated IoT data variance will not affect Kryptein’s accuracy in a long term usage, and Krpytein is also able to support basic analytics tasks like machine learning (e.g., classification).


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Faculty/School / Institute/Centre: Current - Institute for Resilient Regions
Date Deposited: 20 Sep 2021 02:10
Last Modified: 04 Nov 2021 02:15
Uncontrolled Keywords: Compressive sensing, security, encryption, Internet of Things
Fields of Research (2008): 08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4699 Other information and computing sciences > 469999 Other information and computing sciences not elsewhere classified
Socio-Economic Objectives (2020): 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences
Identification Number or DOI: https://doi.org/10.1109/TMC.2020.2992737
URI: http://eprints.usq.edu.au/id/eprint/43677

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