5 papers
General Hazard Detection
Stephanie Ng, CP Lim, SueJen Looi +5
Hazard, as an abstract concept, is typically defined through cognitive-level logical reasoning rather than concrete examples. In contrast, existing hazard detection systems rely on…
NADD: Amplifying Noise for Effective Diffusion-based Adversarial Purification
David D. Nguyen, The-Anh Ta, Yansong Gao +1
The strategy of combining diffusion-based generative models with classifiers continues to demonstrate state-of-the-art performance on adversarial robustness benchmarks. Known as ad…
LLMs Are Not Yet Ready for Deepfake Image Detection
Shahroz Tariq, David Nguyen, M. A. P. Chamikara +3
The growing sophistication of deepfakes presents substantial challenges to the integrity of media and the preservation of public trust. Concurrently, vision-language models (VLMs),…
ThreatModeling-LLM: Automating Threat Modeling using Large Language Models for Banking System
Tingmin Wu, Shuiqiao Yang, Shigang Liu +3
Threat modeling is a crucial component of cybersecurity, particularly for industries such as banking, where the security of financial data is paramount. Traditional threat modeling…
Quantum Down Sampling Filter for Variational Auto-encoder
Farina Riaz, Fakhar Zaman, Hajime Suzuki +2
Variational autoencoders (VAEs) are fundamental for generative modeling and image reconstruction, yet their performance often struggles to maintain high fidelity in reconstructions…