Perceptual Hashing

Perceptual hashing algorithms (PHAs) generate "fingerprints" of images, enabling efficient similarity comparisons while preserving privacy. Current research focuses on evaluating the robustness of various PHAs, including those based on deep learning (like NeuralHash) and traditional computer vision techniques (like DHash), against adversarial attacks and manipulations aimed at evading detection or inferring information from the hash. This field is crucial for applications like identifying illegal online content and protecting intellectual property, but ongoing work highlights significant security and privacy vulnerabilities that need to be addressed for responsible deployment.