Harnessing Generative AI and Large Language Models for Revolutionizing Cybersecurity in the Internet of Things: Ethical and Privacy Implications

Generative artificial intelligence (AI) and large language models (LLMs) have in- troduced transformative capabilities in cybersecurity, particularly in securing Internet of Things (IoT) environments. These technologies can synthesize vast datasets, support real-time anomaly detection, and generate predictive insights through simple prompts. However, their deployment also presents ethical and privacy-related concerns, including algorithmic bias, data leakage, and misuse for malicious content creation. This paper conducts a systematic literature review to evaluate how LLMs and generative AI contribute to IoT cybersecurity. We propose an ethical AI-IoT security framework, examine key challenges, and offer recommendations for integrating responsible AI governance. We aim to inform future research, journal editorial practices, and cybersecurity policy discussions around the dual promise and peril of these technologies

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Publication Details

Journal
Engineering Open Access
Published
2025-06-23
DOI
https://doi.org/10.33140/eoa.03.06.05
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Harnessing Generative AI and Large Language Models for Revolutionizing Cybersecurity in the Internet of Things: Ethical and Privacy Implications

Harsha Sammangi
1 links
Engineering Open Access
Ethics and Social Impacts of AI
article

Harnessing Generative AI and Large Language Models for Revolutionizing Cybersecurity in the Internet of Things: Ethical and Privacy Implications

Harsha Sammangi
article en

Abstract

Generative artificial intelligence (AI) and large language models (LLMs) have in- troduced transformative capabilities in cybersecurity, particularly in securing Internet of Things (IoT) environments. These technologies can synthesize vast datasets, support real-time anomaly detection, and generate predictive insights through simple prompts. However, their deployment also presents ethical and privacy-related concerns, including algorithmic bias, data leakage, and misuse for malicious content creation. This paper conducts a systematic literature review to evaluate how LLMs and generative AI contribute to IoT cybersecurity. We propose an ethical AI-IoT security framework, examine key challenges, and offer recommendations for integrating responsible AI governance. We aim to inform future research, journal editorial practices, and cybersecurity policy discussions around the dual promise and peril of these technologies

Engineering Open AccessVol. 3(6)
Openalex Percentile: Top 76%
Ethics and Social Impacts of AI
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