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Security, Privacy, and Trust of AI-IoT Convergent Smart System
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Author(s): Taye Iyinoluwa Adeyinka (University of Science and Technology, Beijing, China), Kehinde Iyioluwa Adeyinka (University of Science and Technology, Beijing, China)and Ayoade Abolade Emmanuel (Harbin Institute of Technology, Shenzhen, China)
Copyright: 2025
Pages: 32
Source title:
Humans and Generative AI Tools for Collaborative Intelligence
Source Author(s)/Editor(s): Jingyuan Zhao (University of Toronto, Canada), V. Vinoth Kumar (Vellore Institute of Technology, India), Polinpapilinho F. Katina (University of South Carolina Upstate, USA)and Joseph Richards (California State University, Sacramento, USA)
DOI: 10.4018/979-8-3693-8332-2.ch006
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Abstract
Combining AI with IoT transforms conventional systems into highly adaptive, data-driven, and networked intelligent ecosystems. In fact, most of the modernization drives carried out in smart cities, healthcare, manufacturing, and environmental monitoring industries are based on these very AI-IoT systems. AI-IoT integration will hit the future of technology-driven settings pretty fast through improved user experience, efficient management of resources, and real-time decision-making. This chapter covers all security, privacy, and other issues of trust that develop from the convergence of AI with IoT. It provides detailed insights into recent trends and events in privacy-enhancing technologies, such as differential privacy and federated learning. Secure protocol development and trust management schemes cannot be neglected in a trusted AI-IoT ecosystem. .he theoretical and applied approaches, hence opening up ways to some robust and reliable intelligent ecosystems that shall adapt to evolving security and privacy challenges.
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