Trustworthy Pre-Processing of Sensor Data in Data On-chaining Workflows for Blockchain-based IoT Applications

TL;DR

This paper addresses the challenge of ensuring data integrity in blockchain-based IoT applications by proposing trustworthy pre-processing methods using Zero-knowledge Proofs and Trusted Execution Environments, supported by proof-of-concept implementations and evaluations.

Contribution

It introduces a framework for trustworthy pre-processing of sensor data, combining ZKPs and TEEs to enable end-to-end data integrity in data on-chaining workflows.

Findings

Trustworthy pre-processing enhances sensor data integrity.

ZKPs and TEEs are effective for off-chain data validation.

Experimental results show promising performance of proposed methods.

Abstract

Prior to provisioning sensor data to smart contracts, a pre-processing of the data on intermediate off-chain nodes is often necessary. When doing so, originally constructed cryptographic signatures cannot be verified on-chain anymore. This exposes an opportunity for undetected manipulation and presents a problem for applications in the Internet of Things where trustworthy sensor data is required on-chain. In this paper, we propose trustworthy pre-processing as enabler for end-to-end sensor data integrity in data on-chaining workflows. We define requirements for trustworthy pre-processing, present a model and common workflow for data on-chaining, select off-chain computation utilizing Zero-knowledge Proofs (ZKPs) and Trusted Execution Environments (TEEs) as promising solution approaches, and discuss both our proof-of-concept implementations and initial experimental, comparative evaluation results. The importance of trustworthy pre-processing and principle solution approaches are presented, addressing the major problem of end-to-end sensor data integrity in blockchain-based IoT applications.