research-article

Employing Blockchain and Physical Unclonable Functions for Counterfeit IoT Devices Detection

Authors:

Georgios Gketsios,

Nikolaos A. Anagnostopoulos,

Georgios Spathoulas,

Athanasios Kakarountas,

Stefan KatzenbeisserAuthors Info & Claims

COINS '19: Proceedings of the International Conference on Omni-Layer Intelligent Systems

Pages 172 - 178

https://doi.org/10.1145/3312614.3312650

Published: 05 May 2019 Publication History

Abstract

Counterfeit copycat devices have become one of the most important problems in IoT ecosystem. The number of IoT devices manufactured has grown exponentially through last years. In order to be competitive in terms of production cost, they usually need to assemble devices by using ready components built by other manufacturers. This scheme results in a high risk that produced IoT devices do not function properly due to malfunctioning components. This can either be related to component manufacturers trying to minimize costs or even to malicious practices for violating privacy or security of end users of such devices. In this paper a novel approach for preventing such counterfeit copycat practices is presented. The proposed methodology is based on identifying each one of the used components through the use of PUF responses and employing blockchain technology, in order to set-up a platform for tracking the supply chain of both component and IoT devices, without requiring the existence of any central authority.

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Employing Blockchain and Physical Unclonable Functions for Counterfeit IoT Devices Detection

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COINS '19: Proceedings of the International Conference on Omni-Layer Intelligent Systems

May 2019

241 pages

ISBN:9781450366403

DOI:10.1145/3312614

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 05 May 2019

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COINS '19

COINS '19: INTERNATIONAL CONFERENCE ON OMNI-LAYER INTELLIGENT SYSTEMS

May 5 - 7, 2019

Crete, Greece

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https://doi.org/10.1108/BIJ-08-2023-0535
Agiollo ABardhi EConti MDal Fabbro NLazzeretti R(2024)Anonymous Federated Learning via Named-Data NetworkingFuture Generation Computer Systems10.1016/j.future.2023.11.009152:C(288-303)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.future.2023.11.009
Adhikari NRamkumar M(2023)IoT and Blockchain Integration: Applications, Opportunities, and ChallengesNetwork10.3390/network30100063:1(115-141)Online publication date: 24-Jan-2023
https://doi.org/10.3390/network3010006
Gosu PTanguturu RAenugutala SCunha TManjappa K(2023)Decentralised Authentication Protocol for Devices & Users to Access Private Network Services Using Blockchain2023 33rd Conference of Open Innovations Association (FRUCT)10.23919/FRUCT58615.2023.10143051(46-53)Online publication date: 24-May-2023
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Majd NSharko M(2023)Secure and Cost Effective IoT Authentication and Data Storage Framework using Blockchain NFT2023 32nd International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN58024.2023.10230124(1-7)Online publication date: Jul-2023
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