Blockchain-Based and Fuzzy Logic-Enabled False Data Discovery for the Intelligent Autonomous Vehicular System

TL;DR

This paper proposes a novel blockchain and fuzzy logic-based system for detecting false data in autonomous vehicles, enhancing trust, accuracy, and resilience against malicious attacks in vehicular networks.

Contribution

It introduces a blockchain-enabled fuzzy logic approach for false data detection and reputation management in autonomous vehicular systems, addressing limitations of centralized methods.

Findings

Improved false data detection accuracy.

Enhanced trust and reputation management.

Resilience against malicious data injection attacks.

Abstract

Since the beginning of this decade, several incidents report that false data injection attacks targeting intelligent connected vehicles cause huge industrial damage and loss of lives. Data Theft, Flooding, Fuzzing, Hijacking, Malware Spoofing and Advanced Persistent Threats have been immensely growing attack that leads to end-user conflict by abolishing trust on autonomous vehicle. Looking after those sensitive data that contributes to measure the localisation factors of the vehicle, conventional centralised techniques can be misused to update the legitimate vehicular status maliciously. As investigated, the existing centralized false data detection approach based on state and likelihood estimation has a reprehensible trade-off in terms of accuracy, trust, cost, and efficiency. Blockchain with Fuzzy-logic Intelligence has shown its potential to solve localisation issues, trust and false data detection challenges encountered by today's autonomous vehicular system. The proposed Blockchain-based fuzzy solution demonstrates a novel false data detection and reputation preservation technique. The illustrated proposed model filters false and anomalous data based on the vehicles' rules and behaviours. Besides improving the detection accuracy and eliminating the single point of failure, the contributions include appropriating fuzzy AI functions within the Road-side Unit node before authorizing status data by a Blockchain network. Finally, thorough experimental evaluation validates the effectiveness of the proposed model.