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Data Privacy Based on IoT Device Behavior Control Using Blockchain

Published:05 January 2021Publication History
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Abstract

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.

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        • Published in

          cover image ACM Transactions on Internet Technology
          ACM Transactions on Internet Technology  Volume 21, Issue 1
          Visions Paper, Regular Papers, SI: Blockchain in E-Commerce, and SI: Human-Centered Security, Privacy, and Trust in the Internet of Things
          February 2021
          534 pages
          ISSN:1533-5399
          EISSN:1557-6051
          DOI:10.1145/3441681
          • Editor:
          • Ling Liu
          Issue’s Table of Contents

          Copyright © 2021 ACM

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 5 January 2021
          • Accepted: 1 November 2020
          • Revised: 1 September 2020
          • Received: 1 June 2020
          Published in toit Volume 21, Issue 1

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