Security Risks Concerns of Generative AI in the IoT

Autor:	Xu, Honghui, Li, Yingshu, Balogun, Olusesi, Wu, Shaoen, Wang, Yue, Cai, Zhipeng
Rok vydání:	2024
Předmět:	Computer Science - Cryptography and Security Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	In an era where the Internet of Things (IoT) intersects increasingly with generative Artificial Intelligence (AI), this article scrutinizes the emergent security risks inherent in this integration. We explore how generative AI drives innovation in IoT and we analyze the potential for data breaches when using generative AI and the misuse of generative AI technologies in IoT ecosystems. These risks not only threaten the privacy and efficiency of IoT systems but also pose broader implications for trust and safety in AI-driven environments. The discussion in this article extends to strategic approaches for mitigating these risks, including the development of robust security protocols, the multi-layered security approaches, and the adoption of AI technological solutions. Through a comprehensive analysis, this article aims to shed light on the critical balance between embracing AI advancements and ensuring stringent security in IoT, providing insights into the future direction of these intertwined technologies. Comment: 6 pages, 2 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2404.00139 Zobrazit plný text záznamu View this record from Arxiv