Citation

Mehmood, Thabit and Attaullah, Hafiz Muhammad and Ibrahim, Mahmoud and Al Shehry, Mohammad Bin Jaber (2025) Securing AGI-Driven Drone Communications for Climate Change. Artificial General Intelligence-Based Drones for Climate Change. pp. 97-152. ISSN 2327-0411

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Abstract

This chapter provides a comprehensive review of deep learning-based intrusion detection systems for securing Artificial General Intelligence driven drone communications in climate change applications. We examine the evolution of UAV security from basic cryptographic methods to sophisticated AI-driven approaches, with emphasis on the unique requirements of climate applications operating in challenging environments. The chapter explores foundational security mechanisms before analyzing advanced DL architectures, including CNN, LSTM, hybrid approaches, and graph neural networks for swarm security. The discussion encompasses cutting-edge paradigms such as Zero Trust-Architecture, post-quantum-cryptography, and AGI safety considerations essential for autonomous systems. It concludes with a research agenda addressing quantum-resistant, federated learning, self-adaptive architectures, and formal verification methods providing a framework for addressing security challenges at the critical intersection of AGI, drone tech, and climate applications.

Item Type:	Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	30 Jun 2025 08:33
Last Modified:	30 Jun 2025 08:33
URII:	http://shdl.mmu.edu.my/id/eprint/14185

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