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

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