defense arXiv Nov 13, 2025 · Nov 2025
Aditya Mehta, Swarnim Chaudhary, Pratik Narang et al. · Birla Institute of Technology and Science
Detects deepfakes by expanding RGB to 31-channel hyperspectral representation, amplifying artifacts invisible to RGB-based detectors
Output Integrity Attack visiongenerative
Modern generative and diffusion models produce highly realistic images that can mislead human perception and even sophisticated automated detection systems. Most detection methods operate in RGB space and thus analyze only three spectral channels. We propose HSI-Detect, a two-stage pipeline that reconstructs a 31-channel hyperspectral image from a standard RGB input and performs detection in the hyperspectral domain. Expanding the input representation into denser spectral bands amplifies manipulation artifacts that are often weak or invisible in the RGB domain, particularly in specific frequency bands. We evaluate HSI-Detect across FaceForensics++ dataset and show the consistent improvements over RGB-only baselines, illustrating the promise of spectral-domain mapping for Deepfake detection.
transformer gan diffusion Birla Institute of Technology and Science
ML Security Papers