Encrypted Algorithm Detector in Cryptography

Abstract

With the increasing reliance on digital communication and data storage, the need for secure cryptographic algorithms has become paramount. However, the rise of encrypted malware and unauthorized encrypted communications poses a significant challenge to cybersecurity. This paper presents an Encrypted Algorithm Detector using Cryptography, a system designed to verifying and identify encryption algorithms embedded within data transmissions or software applications. The proposed system leverages cryptographic fingerprinting techniques, statistical analysis, and machine learning models to detect and classify encryption methods such as AES, RSA, DES, and other cryptographic schemes. The detector functions by analyzing entropy levels, byte distribution, and frequency patterns to distinguish between encrypted and non-encrypted data. This approach can be applied in cybersecurity for malware detection, forensic investigations, and preventing unauthorized encrypted data transmission in secure environments. The implementation of this system contributes to strengthening cybersecurity measures by enabling early detection of encrypted threats and ensuring compliance with security protocols.