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With the advent of sophisticated artificial intelligence (AI) technologies,the proliferation of deepfakes and the spread of m/disinformation have emergedas formidable threats to the integrity of information ecosystems worldwide.This paper provides an overview of the current literature. Within the frontierAI's crucial application in developing defense mechanisms for detectingdeepfakes, we highlight the mechanisms through which generative AI based onlarge models (LM-based GenAI) craft seemingly convincing yet fabricatedcontents. We explore the multifaceted implications of LM-based GenAI onsociety, politics, and individual privacy violations, underscoring the urgentneed for robust defense strategies. To address these challenges, in this study,we introduce an integrated framework that combines advanced detectionalgorithms, cross-platform collaboration, and policy-driven initiatives tomitigate the risks associated with AI-Generated Content (AIGC). By leveragingmulti-modal analysis, digital watermarking, and machine learning-basedauthentication techniques, we propose a defense mechanism adaptable to AIcapabilities of ever-evolving nature. Furthermore, the paper advocates for aglobal consensus on the ethical usage of GenAI and implementing cyber-wellnesseducational programs to enhance public awareness and resilience againstm/disinformation. Our findings suggest that a proactive and collaborativeapproach involving technological innovation and regulatory oversight isessential for safeguarding netizens while interacting with cyberspace againstthe insidious effects of deepfakes and GenAI-enabled m/disinformationcampaigns.

Deepfakes, Misinformation, and Disinformation in the Era of Frontier AI, Generative AI, and Large AI Models