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Computer security -- Study and teaching

 Subject

Subject Source: Other

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Penetration testing on AI-generated impersonating using spoofing, voice cloning, and real-time deepfaking, 2025

 Item — Call number MU Thesis Sin
Identifier: b7932420
Abstract AI-driven phishing, spoofing, and deepfake attacks pose escalating risks across email systems, educational platforms, and digital social spaces. Publicly available tools now enable adversaries to generate convincing impersonations, bypass conventional defenses, and exploit human trust through email spoofing, voice cloning, and real-time face swapping. These threats highlight the limitations of traditional security awareness training and automated filters when faced with adaptive,...
Dates: 2025