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20242026
most citedA Lightweight and Interpretable Deepfakes Detection Framework

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Uncertainty-Aware Deepfake Detection via Multi-View Structural Learning

Muhammad Umar Farooq, Kutub Uddin, Awais Khan +1

Security-critical biometric and forensic applications require accurate predictions and reliable confidence estimates, particularly under distribution shift. This challenge is espec…

cs.SD2026

TRACE: Training-Free Partial Audio Deepfake Detection via Embedding Trajectory Analysis of Speech Foundation Models

Awais Khan, Muhammad Umar Farooq, Kutub Uddin +1

Partial audio deepfakes, where synthesized segments are spliced into genuine recordings, are particularly deceptive because most of the audio remains authentic. Existing detectors…

cs.SD2025

Adversarial Attacks on Audio Deepfake Detection: A Benchmark and Comparative Study

Kutub Uddin, Muhammad Umar Farooq, Awais Khan +1

The widespread use of generative AI has shown remarkable success in producing highly realistic deepfakes, posing a serious threat to various voice biometric applications, including…

cs.SD2025

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks

Kutub Uddin, Awais Khan, Muhammad Umar Farooq +1

Audio plays a crucial role in applications like speaker verification, voice-enabled smart devices, and audio conferencing. However, audio manipulations, such as deepfakes, pose sig…

cs.CV2025★ 1 cited

A Lightweight and Interpretable Deepfakes Detection Framework

Muhammad Umar Farooq, Ali Javed, Khalid Mahmood Malik +1

The recent realistic creation and dissemination of so-called deepfakes poses a serious threat to social life, civil rest, and law. Celebrity defaming, election manipulation, and de…

cs.SD2025

Transferable Adversarial Attacks on Audio Deepfake Detection

Muhammad Umar Farooq, Awais Khan, Kutub Uddin +1

Audio deepfakes pose significant threats, including impersonation, fraud, and reputation damage. To address these risks, audio deepfake detection (ADD) techniques have been develop…

cs.CV2024

Securing Social Media Against Deepfakes using Identity, Behavioral, and Geometric Signatures

Muhammad Umar Farooq, Awais Khan, Ijaz Ul Haq +1

Trust in social media is a growing concern due to its ability to influence significant societal changes. However, this space is increasingly compromised by various types of deepfak…