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

arXiv: https://arxiv.org/abs/2110.15869 · HTML: https://mlsanity.com/paper/2110.15869/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Oct 2021.

## Built on by (most cited first, 1 of 1)

- [End-to-End Verifiable Decentralized Federated Learning](https://mlsanity.com/paper/2404.12623/) (2024)

## Abstract (arXiv)

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.