Advancements in AI for Deepfake Attacks Detection and Prevention
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Advancements in AI for Deepfake Attacks Detection and Prevention
Authors:
Sandeep Phanireddy
Abstract: 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.
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