World War II Era Cipher

World War II-era ciphers are the subject of ongoing research focusing on automated decryption and classification techniques. Current efforts leverage machine learning, including support vector machines, random forests, and deep learning models like convolutional neural networks and recurrent neural networks, to analyze ciphertext features and identify cipher types with high accuracy, even with limited data. This research contributes to both historical cryptography understanding and informs modern cybersecurity by providing insights into the strengths and weaknesses of various encryption methods and developing new approaches for automated cryptanalysis. Furthermore, the application of large language models to decipher ciphers and even to simulate penetration testing scenarios is a growing area of investigation.