Data Privacy Based on IoT Device Behavior Control Using Blockchain

Loukil, Faiza, Ghedira-Guegan, Chirine, Boukadi, Khouloud, Benharkat, Aïcha-Nabila and BENKHELIFA, Elhadj (2021) Data Privacy Based on IoT Device Behavior Control Using Blockchain. ACM Transactions on Internet Technology, 21 (1). pp. 1-20. ISSN 1533-5399

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Abstract or description

The Internet of Things (IoT) is expected to improve the individuals’ quality of life. However, ensuring security and privacy in the IoT context is a non-trivial task due to the low capability of these connected devices.
Generally, the IoT device management is based on a centralized entity that validates communication and connection rights. Therefore, this centralized entity can be considered as a single point of failure. Yet, in the case of distributed approaches, it is difficult to delegate the right validation to IoT devices themselves in untrustworthy IoT environments. Fortunately, the blockchain may provide decentralization of overcoming the trust problem while designing a privacy-preserving system. To this end, we propose a novel privacy-preserving IoT device management framework based on the blockchain technology. In the proposed system, the IoT devices are controlled by several smart contracts that validate the connection rights according to the privacy permission settings predefined by the data owners and the stored record array of detected misbehavior of each IoT device. In fact, smart contracts can immediately detect the devices that have vulnerabilities and have been hacked or pose a threat to the IoT network. Therefore, the data owner’s privacy is preserved by enforcing the control over the own devices. For validation purposes, we deploy the proposed solution on a private Ethereum blockchain and give the performance evaluation

Item Type:	Article
Uncontrolled Keywords:	: Behavior Control, Blockchain, Smart Contract, Internet of Things
Faculty:	School of Digital, Technologies and Arts > Computer Science, AI and Robotics
Depositing User:	Elhadj BENKHELIFA
Date Deposited:	29 Nov 2022 15:13
Last Modified:	24 Feb 2023 14:04
URI:	https://eprints.staffs.ac.uk/id/eprint/7502

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