Generative AI-Powered Cybersecurity Threats: A Growing Concern

With the advancement of generative AI (GenAI) models, new cybersecurity risks have surfaced of which including threats such as GenAI-driven phishing and deepfakes. Exacerbating the issue herein is that existing security methods and frameworks largely struggle to address these evolving attack vectors, thus making the case for adaptive mitigation strategies. This study analyzes emerging GenAI cyber threats, real-world cases, and defense mechanisms, using thematic analysis to categorize risks and solutions. It highlights the need for further studies in developing advanced threat detection methods, fortifying AI governance, and interdisciplinary collaboration, and focusing on advancing explainable AI, adversarial training, and regulatory enforcement to balance security and innovation. This research aims to strengthen our defenses against GenAI cyber threats and safeguard our digital landscape.

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Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-08-15
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
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article

Generative AI-Powered Cybersecurity Threats: A Growing Concern

Journal of the Association for Information Systems
Adversarial Robustness in Machine Learning
article

Generative AI-Powered Cybersecurity Threats: A Growing Concern

article en

Abstract

With the advancement of generative AI (GenAI) models, new cybersecurity risks have surfaced of which including threats such as GenAI-driven phishing and deepfakes. Exacerbating the issue herein is that existing security methods and frameworks largely struggle to address these evolving attack vectors, thus making the case for adaptive mitigation strategies. This study analyzes emerging GenAI cyber threats, real-world cases, and defense mechanisms, using thematic analysis to categorize risks and solutions. It highlights the need for further studies in developing advanced threat detection methods, fortifying AI governance, and interdisciplinary collaboration, and focusing on advancing explainable AI, adversarial training, and regulatory enforcement to balance security and innovation. This research aims to strengthen our defenses against GenAI cyber threats and safeguard our digital landscape.

Journal of the Association for Information Systems
Kennesaw State University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 72%
Adversarial Robustness in Machine Learning
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Generative AI-Powered Cybersecurity Threats: A Growing Concern · Journal of the Association for Information Systems (2025) | TGRS Research Map | TGRS