Advancements in AI for Deepfake attacks Detection and prevention

Deepfake technology has rapidly evolved, raising significant ethical, security, and societal

concerns. By leveraging deep learning models, malicious actors can create highly realistic fake videos and

audio clips, making it increasingly difficult to distinguish between real and manipulated content. This

paper explores the mechanics behind deepfake creation, its implications in misinformation, fraud, and

identity theft, and the challenges in detecting and mitigating such threats. Through a discussion on

detection techniques, legal frameworks, and public awareness initiatives, this study highlights the need

for a multi-layered defense against deepfake-related risks. As deepfake technology continues to advance,

a combination of technological, legal, and educational strategies is crucial to safeguarding digital

authenticity.

Keywords: Deepfake, artificial intelligence, misinformation, media manipulation, cybersecurity, deep

learning, fraud detection, digital authenticity, adversarial networks, identity theft.