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Title: Privacy-preserving blockchain based IoT ecosystem using attribute-based encryption
Authors: Rahulamathavan, Yogachandran
Phan, Raphael C.-W.
Rajarajan, Muttukrishnan
Misra, Sudip
Kondoz, Ahmet
Keywords: Privacy
Security
Internet of things
Blockchain
Attribute based encryption
Issue Date: 2018
Publisher: IEEE
Citation: RAHULAMATHAVAN, Y. ... et al., 2018. Privacy-preserving blockchain based IoT ecosystem using attribute-based encryption. Presented at the 11th IEEE International Conference on Advanced Networks and Telecommunications Systems, (ANTS 2017), Bhubaneswar, India, 17-20 Dec.
Abstract: © 2017 IEEE. The Internet of Things (IoT) has penetrated deeply into our lives and the number of IoT devices per person is expected to increase substantially over the next few years. Due to the characteristics of IoT devices (i.e., low power and low battery), usage of these devices in critical applications requires sophisticated security measures. Researchers from academia and industry now increasingly exploit the concept of blockchains to achieve security in IoT applications. The basic idea of the blockchain is that the data generated by users or devices in the past are verified for correctness and cannot be tampered once it is updated on the blockchain. Even though the blockchain supports integrity and non-repudiation to some extent, confidentiality and privacy of the data or the devices are not preserved. The content of the data can be seen by anyone in the network for verification and mining purposes. In order to address these privacy issues, we propose a new privacy-preserving blockchain architecture for IoT applications based on attribute-based encryption (ABE) techniques. Security, privacy, and numerical analyses are presented to validate the proposed model.
Description: 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.
Version: Accepted for publication
DOI: 10.1109/ANTS.2017.8384164
URI: https://dspace.lboro.ac.uk/2134/36325
Publisher Link: https://doi.org/10.1109/ANTS.2017.8384164
ISBN: 9781538623473
Appears in Collections:Conference Papers and Presentations (Loughborough University London)

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