Data Provenance for Secure Internet of Things: A Privacy-Preserving Protocol for Secure Data Provenance in IoT Systems

Abstract

Data provenance to maintain data integrity and authenticity is a significant challenge in the Internet of Things (IoT) environments. Additionally, if the provenance metadata itself can be communicated in a privacy preserving manner, it expands the usage of IoT systems to human societal domains where privacy is of paramount importance. These papers present a scheme to combine data provenance and privacy-preserving solutions. Proposed scheme merges Physical Unclonable Function (PUF) technology with non-interactive zero-knowledge proof to provide trustworthy and dependable IoT systems. In this context, the IoT device can anonymously send data to the corresponding server associated with the proof of ownership. Proposed 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.