96 citations · 197 across the 14 of their papers we have counts for
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Quality-Agnostic Deepfake Detection with Intra-model Collaborative Learning
Binh M. Le, Simon S. Woo
Deepfake has recently raised a plethora of societal concerns over its possible security threats and dissemination of fake information. Much research on deepfake detection has been…
Unveiling Vulnerabilities in Interpretable Deep Learning Systems with Query-Efficient Black-box Attacks
Eldor Abdukhamidov, Mohammed Abuhamad, Simon S. Woo +2
Deep learning has been rapidly employed in many applications revolutionizing many industries, but it is known to be vulnerable to adversarial attacks. Such attacks pose a serious t…
HRFNet: High-Resolution Forgery Network for Localizing Satellite Image Manipulation
Fahim Faisal Niloy, Kishor Kumar Bhaumik, Simon S. Woo
Existing high-resolution satellite image forgery localization methods rely on patch-based or downsampling-based training. Both of these training methods have major drawbacks, such…
Microbial Genetic Algorithm-based Black-box Attack against Interpretable Deep Learning Systems
Eldor Abdukhamidov, Mohammed Abuhamad, Simon S. Woo +2
Deep learning models are susceptible to adversarial samples in white and black-box environments. Although previous studies have shown high attack success rates, coupling DNN models…
CFL-Net: Image Forgery Localization Using Contrastive Learning
Fahim Faisal Niloy, Kishor Kumar Bhaumik, Simon S. Woo
Conventional forgery localizing methods usually rely on different forgery footprints such as JPEG artifacts, edge inconsistency, camera noise, etc., with cross-entropy loss to loca…
Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors
Hasam Khalid, Minha Kim, Shahroz Tariq +1
Significant advancements made in the generation of deepfakes have caused security and privacy issues. Attackers can easily impersonate a person's identity in an image by replacing…