Open Access

ARTICLE

Cybersecurity Threat Modeling and Privacy Risk Assessment in Collaborative Civilian UAV Systems

Ahmed Murtaza¹, Abdullah Memon², Sana Hafeez³, Muzammil Ali², Ghulam E Mustafa Abro^4,*

1 Department of Information Technology, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Pakistan
2 Department of Control & Instrumentation Engineering, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia
3 Digital Innovation Research Institute, School of Computer Science & Mathematics, Liverpool John Moores University, Liverpool, UK
4 Research Unit for Robophilosophy and Integrative Social Robotics (RISR), Aarhus University, Aarhus, Denmark

* Corresponding Author: Ghulam E Mustafa Abro. Email:

Intelligent Automation & Soft Computing 2026, 41, 49-72. https://doi.org/10.32604/iasc.2026.082765

Received 22 March 2026; Accepted 15 July 2026; Issue published 28 August 2026

Abstract

Civilian Unmanned Aerial Systems (UAS) are increasingly deployed in smart-city monitoring, infrastructure inspection, logistics, and emergency response applications. However, their integration with wireless networks, cloud services, and AI-driven analytics significantly expands cybersecurity and privacy risks. Existing studies mainly focus on isolated technical vulnerabilities such as GNSS spoofing, jamming, and communication attacks, while lacking a unified framework that systematically connects cyber threats with quantitative privacy risk assessment. To address this research gap, this study proposes a layered threat-modeling framework for collaborative civilian UAS based on multidimensional attack-surface analysis and STRIDE-oriented threat mapping. In addition, a quantitative privacy risk model is developed by integrating compromise likelihood, data sensitivity, contextual amplification, downstream misuse potential, and regulatory exposure. The proposed framework is evaluated through three representative deployment scenarios: smart-city surveillance, critical infrastructure monitoring, and mega-event security operations. The findings demonstrate that technical compromises in UAS ecosystems can propagate into large-scale societal and privacy harms, particularly in highly connected urban environments. The study contributes a structured cybersecurity and privacy assessment methodology, a UAS-specific privacy risk quantification model, and engineering as well as governance-oriented mitigation strategies to support resilient, privacy-aware, and regulation-compliant civilian UAS deployment.

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Keywords

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