Kgs Muhammad Farhan Rabbaniansyah
Politeknik Negeri Sriwijaya

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Implementation of Ethereum-Based Blockchain Technology for ADS-B Data Security and Validation Kgs Muhammad Farhan Rabbaniansyah; Lindawati Lindawati; Sopian Soim
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): June
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.271

Abstract

Automatic Dependent Surveillance–Broadcast (ADS-B) has significantly enhanced air traffic monitoring by enabling real-time broadcasting of aircraft positions and identifiers. However, it is intrinsically susceptible to spoofing, replay, and tampering attacks because to its lack of cryptographic protections. This paper introduces a blockchain-based ADS-B validation system for safe, decentralized data authentication that makes use of Ethereum smart contracts and MetaMask. The suggested system uses Solidity-coded rules to enforce logical limitations on altitude changes, timestamp order, and geographic displacement in order to validate incoming flight messages. Every data transaction is protected by two layers of security: the smart contract's automated detection and MetaMask's manual permission. This combines operational control with the immutability of blockchain technology by guaranteeing that even reported anomalies cannot be committed without human consent. The OpenSky Network flight data was used to test the system, and 56 attack simulations in the spoofing, replay, and tampering categories were run. All accepted anomalies were purposefully allowed to test forensic transparency, and the contract obtained a 92.9% detection rate. All transaction information were retained in Ethereum's transparent ledger, enhancing its suitability for incident investigation and regulatory compliance. The findings support blockchain's applicability in preventing unwanted changes to aircraft telemetry. Stricter timestamp constraints, machine learning for anomaly detection, and interaction with international aircraft registries to better spoofing detection are possible future improvements. This approach combines the practical needs of air traffic with the potential advantages of blockchain technology.