Proceedings of 1st GENZERO Workshop
Revolutionizing Autonomous Systems Security with Generative AI, and Large Language Models for Zero Trust Architecture
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Product details:
- Publisher Springer Nature Singapore
- Date of Publication 22 October 2025
- Number of Volumes 1 pieces, Book
- ISBN 9789819510498
- Binding Hardback
- No. of pages228 pages
- Size 235x155 mm
- Language English
- Illustrations XIII, 228 p. 72 illus., 65 illus. in color. 700
Categories
Probability and mathematical statistics
Civil and construction engineering
Traffic engineering sciences, automotive and transportation industry
System analysis, system planning
Data management in computer systems
Operating systems and graphical user interfaces
Artificial Intelligence
Privacy, data security
Physics in general
Vehicles in general
Probability and mathematical statistics (charity campaign)
Civil and construction engineering (charity campaign)
Traffic engineering sciences, automotive and transportation industry (charity campaign)
System analysis, system planning (charity campaign)
Data management in computer systems (charity campaign)
Operating systems and graphical user interfaces (charity campaign)
Artificial Intelligence (charity campaign)
Privacy, data security (charity campaign)
Physics in general (charity campaign)
Vehicles in general (charity campaign)
Long description:
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This Open Access volume compiles peer-reviewed research at the GENZERO Workshop on Security and Autonomous Systems, hosted by the Technology Innovation Institute in Abu Dhabi in November 2024. As a leading event in the fields of security of autonomous systems and generative AI, the workshop emphasizes the expansion of Zero Trust architecture across a variety of autonomous platforms. It highlights the critical importance of protecting Physical AI systems—such as drones, unmanned ground vehicles (UGVs), and humanoid robots—from cyberattacks, which have the potential to cause significant harm. The proceedings feature theoretical models, practical frameworks, and real-world applications of large language models and other generative AI techniques aimed at enhancing security, resilience, and intelligence in UAV collectives, robotics, and other autonomous systems.
Ensuring security has become a paramount challenge as these systems become increasingly complex and self-directed. The studies presented here focus on breakthroughs in distributed intelligence, secure communications, and real-time anomaly detection, offering actionable strategies for aerospace, defense, and critical infrastructure industries. Forward-looking discussions also explore how machine learning and AI-driven approaches could redefine safety and security standards, particularly in autonomous decision-making and continuous operations. Collectively, this volume provides invaluable insights for researchers, practitioners, and policymakers working toward robust and trustworthy autonomous solutions while also addressing pressing challenges and emerging opportunities in this rapidly evolving field.
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