Dictionary Attack

Dictionary attacks exploit the reuse of common elements (passwords, biometric templates, or even facial features) across multiple accounts or individuals to compromise security systems. Current research focuses on developing and refining these attacks using various machine learning models, including deep learning architectures like generative adversarial networks and recurrent neural networks, to improve their effectiveness against diverse authentication methods such as passwords, iris recognition, gait analysis, and facial recognition. This research highlights vulnerabilities in existing security systems and drives the development of more robust and resilient authentication mechanisms across various biometric and knowledge-based authentication systems.