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Addressing Trust Challenges in Blockchain Oracles Using Asymmetric Byzantine Quorums

Fahad Rahman, Chafiq Titouna, Farid Nait-Abdesselam

TL;DR

The paper tackles the challenge of trustworthy data feed from external sources into Smart Contracts by introducing Asymmetric Byzantine Quorums (ABQ), a Byzantine fault-tolerant framework for Blockchain Oracles, augmented with a heuristic detection layer for auditability. ABQ uses quorum-based aggregation with a longest-chain rule to derive Oracle values, leveraging properties such as $(N_p+f_p)/2$ and $|Q|>3F_m$ to tolerate Byzantine faults. Empirical results on two real-world IoT temperature datasets show ABQ achieving higher accuracy and F1 scores than established baselines, with statistical significance ($p<0.05$) and robustness demonstrated through reliability analysis. The approach aims to improve trust, scalability, and transparency of Oracles in both public and private Blockchains, with potential for broader real-world deployment in DApps and automated systems.

Abstract

Distributed Computing in Blockchain Technology (BCT) hinges on a trust assumption among independent nodes. Without a third-party interface or what is known as a Blockchain Oracle, it can not interact with the external world. This Oracle plays a crucial role by feeding extrinsic data into the Blockchain, ensuring that Smart Contracts operate accurately in real time. The Oracle problem arises from the inherent difficulty in verifying the truthfulness of the data sourced by these Oracles. The genuineness of a Blockchain Oracle is paramount, as it directly influences the Blockchain's reliability, credibility, and scalability. To tackle these challenges, a strategy rooted in Byzantine fault tolerance φ is introduced. Furthermore, an autonomous system for sustainability and audibility, built on heuristic detection, is put forth. The effectiveness and precision of the proposed strategy outperformed existing methods using two real-world datasets, aimed to meet the authenticity standards for Blockchain Oracles.

Addressing Trust Challenges in Blockchain Oracles Using Asymmetric Byzantine Quorums

TL;DR

The paper tackles the challenge of trustworthy data feed from external sources into Smart Contracts by introducing Asymmetric Byzantine Quorums (ABQ), a Byzantine fault-tolerant framework for Blockchain Oracles, augmented with a heuristic detection layer for auditability. ABQ uses quorum-based aggregation with a longest-chain rule to derive Oracle values, leveraging properties such as and to tolerate Byzantine faults. Empirical results on two real-world IoT temperature datasets show ABQ achieving higher accuracy and F1 scores than established baselines, with statistical significance () and robustness demonstrated through reliability analysis. The approach aims to improve trust, scalability, and transparency of Oracles in both public and private Blockchains, with potential for broader real-world deployment in DApps and automated systems.

Abstract

Distributed Computing in Blockchain Technology (BCT) hinges on a trust assumption among independent nodes. Without a third-party interface or what is known as a Blockchain Oracle, it can not interact with the external world. This Oracle plays a crucial role by feeding extrinsic data into the Blockchain, ensuring that Smart Contracts operate accurately in real time. The Oracle problem arises from the inherent difficulty in verifying the truthfulness of the data sourced by these Oracles. The genuineness of a Blockchain Oracle is paramount, as it directly influences the Blockchain's reliability, credibility, and scalability. To tackle these challenges, a strategy rooted in Byzantine fault tolerance φ is introduced. Furthermore, an autonomous system for sustainability and audibility, built on heuristic detection, is put forth. The effectiveness and precision of the proposed strategy outperformed existing methods using two real-world datasets, aimed to meet the authenticity standards for Blockchain Oracles.
Paper Structure (19 sections, 17 equations, 16 figures, 10 tables, 2 algorithms)

This paper contains 19 sections, 17 equations, 16 figures, 10 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Related Work
  3. System Model
  4. Methodology
  5. Establishment of ABQs and Determining Oracle Values
  6. BQ Primary ($1^{st}$) Property
  7. BQ's Secondary ($2^{nd}$) Property
  8. BQ's Tertiary ($3^{rd}$) Property
  9. Detection of faulty/ compromised Device(s)
  10. Simulations and Results
  11. Data Set
  12. Evaluation
  13. Analysis of Statistical Hypotheses
  14. Reliability Analysis
  15. Absolute Improvement
  16. ...and 4 more sections

Figures (16)

  • Figure 1: Data transition, real-world to Blockchain
  • Figure 2: Data transmission and processing: Field to Blockchain through Oracle
  • Figure 3: Three Characteristics/ properties of BQ
  • Figure 4: Rule of the Longest Chain for Quorum Formation
  • Figure 5: State transition diagram of proposed model
  • ...and 11 more figures