ISSN :3049-2335

ZAPS: A Zero Knowledge Proof Protocol for Secure UAV Authentication with Flight Path Privacy

Original Research (Published On: 26-Jun-2025 )
DOI : https://dx.doi.org/10.54364/cybersecurityjournal.2025.1112

Shayesta Naziri, Xu Wang, Guangsheng Yu, Christy Liang and Wei Ni

Adv. Know. Base. Syst. Data Sci. Cyber., 2 (2):236-259

Shayesta Naziri : School of Computer Science, University of Technology Sydney, NSW, 2007, AUS

Xu Wang : School of Electrical and Data Engineering, University of Technology Sydney

Guangsheng Yu : School of Electrical and Data Engineering, University of Technology Sydney

Christy Liang : School of Computer Science, University of Technology Sydney

Wei Ni : School of Electrical and Data Engineering, University of Technology Sydney

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DOI: https://dx.doi.org/10.54364/cybersecurityjournal.2025.1112

Article History: Received on: 27-Apr-25, Accepted on: 19-Jun-25, Published on: 26-Jun-25

Corresponding Author: Shayesta Naziri

Email: shayesta.naziri@student.uts.edu.au

Citation: Shayesta Naziri (2025). ZAPS: A Zero Knowledge Proof Protocol for Secure UAV Authentication with Flight Path Privacy. Adv. Know. Base. Syst. Data Sci. Cyber., 2 (2 ):236-259


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Abstract

    

Abstract—The increasing deployment of Unmanned Aerial Vehicles (UAVs) for military, commercial, and logistics applications has raised significant concerns regarding flight path privacy. Conventional UAV communication systems often expose flight path data to third parties, making them vulnerable to tracking, surveillance, and location inference attacks. Existing encryption techniques provide security but fail to ensure complete privacy, as adversaries can still infer movement patterns through metadata analysis. To address these challenges, we propose a zk-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge)-based privacy preserving flight path authentication and verification framework. Our approach ensures that a UAV can prove its authorisation, validate its flight path with a control centre, and comply with regulatory constraints without revealing any sensitive trajectory information. By leveraging zk-SNARKs, the UAV can generate cryptographic proofs that verify compliance with predefined flight policies while keeping the exact path and location undisclosed. This method mitigates risks associated with real-time tracking, identity exposure, and unauthorised interception, thereby enhancing UAV operational security in adversarial environments. Our proposed solution balances privacy, security, and computational efficiency, making it suitable for resource-constrained UAVs in both civilian and military applications.

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