Authors : Nischal S Hiremath; Sanchit Srinivas; Aniket P; Parthivi R; Shobha T

Volume/Issue : Volume 10 - 2025, Issue 1 - January

Google Scholar : https://tinyurl.com/4pncphtz

Scribd : https://tinyurl.com/3a4ku2rz

DOI : https://doi.org/10.5281/zenodo.14717006

Abstract : Integrating AI with IoT has formed the concept of AIoT systems that work to really increase automation, data analytics, and decision- making procedures. But fusion has also emerged with its challenges to new security issues for AIoT systems. Threats such as data breaches, unauthorized access, manipulation of AI models, and privacy issues affect these systems. Most of these vulnerabilities stem from the intricate integration of AI algorithms with IoT devices, thus being poorly secured in many of them. This paper investigates a few of the most common security risks found in AIoT systems: insecure data transmission, weak device authentication, and adversarial attacks against the AI model. It, thereby, opens possible solutions such as secure communication protocols, strengthening of AI model defences, and blockchain-based decentralized security. These challenges have to be challenged to ensure the implementation of AIoT with security in its sights both in healthcare and smart city applications as well as industrial automation sectors.

Keywords : AIoT Features, Blockchain, OAuth in Machine Learning.

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