  With the advent of sophisticated artificial intelligence (AI) technologies,
the proliferation of deepfakes and the spread of m/disinformation have emerged
as formidable threats to the integrity of information ecosystems worldwide.
This paper provides an overview of the current literature. Within the frontier
AI's crucial application in developing defense mechanisms for detecting
deepfakes, we highlight the mechanisms through which generative AI based on
large models (LM-based GenAI) craft seemingly convincing yet fabricated
contents. We explore the multifaceted implications of LM-based GenAI on
society, politics, and individual privacy violations, underscoring the urgent
need for robust defense strategies. To address these challenges, in this study,
we introduce an integrated framework that combines advanced detection
algorithms, cross-platform collaboration, and policy-driven initiatives to
mitigate the risks associated with AI-Generated Content (AIGC). By leveraging
multi-modal analysis, digital watermarking, and machine learning-based
authentication techniques, we propose a defense mechanism adaptable to AI
capabilities of ever-evolving nature. Furthermore, the paper advocates for a
global consensus on the ethical usage of GenAI and implementing cyber-wellness
educational programs to enhance public awareness and resilience against
m/disinformation. Our findings suggest that a proactive and collaborative
approach involving technological innovation and regulatory oversight is
essential for safeguarding netizens while interacting with cyberspace against
the insidious effects of deepfakes and GenAI-enabled m/disinformation
campaigns.
