# Security Risks Concerns of Generative AI in the IoT

arXiv: https://arxiv.org/abs/2404.00139 · HTML: https://mlsanity.com/paper/2404.00139/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 31 references that are in the map.
- First posted on arXiv 29 Mar 2024.

## Builds on (most cited first, 3 of 3)

- [From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy](https://mlsanity.com/paper/2307.00691/) (2023)
- [Security and Privacy on Generative Data in AIGC: A Survey](https://mlsanity.com/paper/2309.09435/) (2023)
- [Generative AI for Cyber Threat-Hunting in 6G-enabled IoT Networks](https://mlsanity.com/paper/2303.11751/) (2023)

## Built on by (most cited first, 2 of 2)

- [Generative Artificial Intelligence for Internet of Things Computing: A Systematic Survey](https://mlsanity.com/paper/2504.07635/) (2025)
- [Physics-Inspired Distributed Radio Map Estimation](https://mlsanity.com/paper/2502.00319/) (2025)

## Abstract (arXiv)

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.