Chaotic Speech Encryption Using Logistic Map Function for Key Generation and Encryption/Decryption Operations

In this paper we implement a chaotic speech encryption system to enhance security. The logistic map function (commonly referred to as the "insect population model") is employed to generate cryptographic key pairs for speech encryption and decryption operations. This method improves the computational efficiency of speech encryption systems by leveraging chaotic systems' sensitivity to initial conditions and pseudo-random properties. Key implementation aspects include: - Generation of chaotic sequences using the logistic map equation: xₙ₊₁ = r*xₙ(1-xₙ) - Transformation of chaotic sequences into binary encryption keys through threshold quantization - Application of XOR operations between speech samples and generated keys for encryption - Implementation of synchronized decryption using identical initial parameters The algorithm achieves secure encryption through the chaotic system's inherent unpredictability while maintaining computational efficiency suitable for real-time speech processing applications.