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An FPGA Implementation of Privacy Preserving Data Provenance Model Based on PUF for Secure Internet of Things

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Abstract

Data provenance to maintain data integrity and authenticity is a significant challenge in the Internet of Things (IoT) environments. Data provenance protocols must communicate provenance metadata while preserving its privacy. This enables trust in IoT systems expanding its acceptance within society. In this paper, we present a scheme to combine data provenance and privacy-preserving solutions. Our scheme utilizes Physical Unclonable Functions (PUFs) with non-interactive zero knowledge proof to provide trustworthy and dependable IoT systems. An IoT device can anonymously send data to the corresponding server associated with the proof of ownership. We propose a privacy-preserving data provenance protocol. This protocol was synthesized with Altera Quartus. It was implemented on an Altera Cyclone IV FPGA to demonstrate its practicality and feasibility. Most of the protocol steps take time of the order of 40 \(\upmu\)s establishing its practicality.

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  1. Department of Electrical and Computer Engineering, Iowa State University, Ames, USA

    Hala Hamadeh & Akhilesh Tyagi

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  1. Hala Hamadeh
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  2. Akhilesh Tyagi
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Correspondence to Hala Hamadeh.

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This article is part of the topical collection “Technologies and Components for Smart Cities” guest edited by Himanshu Thapliyal, Saraju P. Mohanty, Srinivas Katkoori and Kailash Chandra Ray.

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Hamadeh, H., Tyagi, A. An FPGA Implementation of Privacy Preserving Data Provenance Model Based on PUF for Secure Internet of Things. SN COMPUT. SCI. 2, 65 (2021). https://doi.org/10.1007/s42979-020-00428-0

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