7 citations · 9 across the 13 of their papers we have counts for
14 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…
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…
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…
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…
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…
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…
Securing Voice Biometrics: One-Shot Learning Approach for Audio Deepfake Detection
Awais Khan, Khalid Mahmood Malik
The Automatic Speaker Verification (ASV) system is vulnerable to fraudulent activities using audio deepfakes, also known as logical-access voice spoofing attacks. These deepfakes p…
Bridging the Spoof Gap: A Unified Parallel Aggregation Network for Voice Presentation Attacks
Awais Khan, Khalid Mahmood Malik
Automatic Speaker Verification (ASV) systems are increasingly used in voice bio-metrics for user authentication but are susceptible to logical and physical spoofing attacks, posing…
Frame-to-Utterance Convergence: A Spectra-Temporal Approach for Unified Spoofing Detection
Awais Khan, Khalid Mahmood Malik, Shah Nawaz
Voice spoofing attacks pose a significant threat to automated speaker verification systems. Existing anti-spoofing methods often simulate specific attack types, such as synthetic o…
Voice Spoofing Countermeasures: Taxonomy, State-of-the-art, experimental analysis of generalizability, open challenges, and the way forward
Awais Khan, Khalid Mahmood Malik, James Ryan +1
Malicious actors may seek to use different voice-spoofing attacks to fool ASV systems and even use them for spreading misinformation. Various countermeasures have been proposed to…