1 citations · 2 across the 10 of their papers we have counts for
11 papers
Exposing and Mitigating Neural Codec Vulnerabilities in Audio Deepfake Detection
Abdullah, Awais Khan, Khalid Mahmood Malik
Existing audio deepfake detection (ADD) datasets and detectors are primarily built for vocoder-based synthesis, evaluated against traditional post-hoc perturbations such as MP3/AAC…
PE-Mamba: Bidirectional Selective Layer Aggregation for AI-Generated Image Detection
Kutub Uddin, Nusrat Tasnim, Khalid Malik
AI-generated image (AIGI) detection has become increasingly challenging due to the rapid advancement of generative models and the diminishing gap between synthetic and authentic co…
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…
Do Transformations Reveal the Truth? Generative Residual Learning for Generalized AI-Generated Image Detection
Kutub Uddin, Nusrat Tasnim, Awais Khan +2
The rapid advancement of generative AI has enabled the creation of highly realistic deepfake media, posing significant threats, including misinformation, digital identity theft, fr…
Dual-Branch Gated Fusion for Open-Set Audio Deepfake Source Tracing
Awais Khan, Kutub Uddin, Khalid Malik
Attributing a synthetic utterance to its originating system remains an open challenge: closed-set models fail to reject unseen synthesizers and produce overconfident predictions. T…
AI-Generated Image Detection: An Empirical Study and Future Research Directions
Nusrat Tasnim, Kutub Uddin, Khalid Mahmood Malik
The threats posed by AI-generated media, particularly deepfakes, are now raising significant challenges for multimedia forensics, misinformation detection, and biometric system res…
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…
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…
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…
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…
Parallel Stacked Aggregated Network for Voice Authentication in IoT-Enabled Smart Devices
Awais Khan, Ijaz Ul Haq, Khalid Mahmood Malik
Voice authentication on IoT-enabled smart devices has gained prominence in recent years due to increasing concerns over user privacy and security. The current authentication system…