🔐 IDENTIFICATION OF CRYPTO USING CIPHERTEXT 📘 Overview This project focuses on identifying the encryption algorithm used to generate a given ciphertext. By analyzing the patterns, frequency, and structure of the ciphertext, the model attempts to determine whether it was encrypted using algorithms like Caesar Cipher, Vigenère Cipher, Substitution Cipher, AES, RSA, etc.
Such identification is useful in cybersecurity, digital forensics, and academic research, especially when dealing with unknown or legacy data.
🧠 Project Goals 🔍 Analyze ciphertexts and detect underlying encryption techniques.
📊 Extract features from ciphertext (frequency, entropy, character distribution).
🤖 Train ML models or use rule-based logic to classify the encryption method.
🔐 Support for both classical and modern ciphers.
🛠️ Features ✔️ Ciphertext analysis using statistical methods.
✔️ Identification of classical encryption types.
✔️ Support for supervised learning models (e.g., Random Forest, SVM).
✔️ Visualizations of character frequency and distribution.
✔️ CLI and (optional) web interface.