An An Analytical Survey of Audio Encryption Techniques (2015 - 2025)

Abstract

This paper presents an analytical survey of audio encryption techniques developed between 2015 and 2025, aiming to evaluate recent advances in secure digital audio communication. The increasing transmission of sensitive audio data through wireless communication, telemedicine, smart systems, and military applications has created a growing need for robust and intelligent audio encryption methods capable of resisting modern cryptanalytic attacks. The survey reviews classical encryption algorithms such as AES, ECC, and SPN-based methods, which provide strong resistance against brute-force attacks but remain limited by their deterministic structure when applied to highly correlated audio signals. In addition, chaos-based and hyper-chaotic encryption models are discussed due to their nonlinear behavior, high sensitivity to initial conditions, and expanded key spaces that improve confusion–diffusion performance and randomness. DNA-based and bio-inspired encryption approaches are also analyzed for their ability to enhance security complexity using biological coding principles combined with chaotic maps. Furthermore, recent neural and neuro-chaotic techniques, including ANN-based models and NeuroChaosCrypt systems, are reviewed. Based on the surveyed studies, hybrid intelligent approaches combining chaos, DNA, and neural learning mechanisms demonstrate stronger security performance, improved randomness, and higher resistance against statistical and differential attacks compared with traditional encryption methods. Finally, this paper highlights current research gaps and discusses future directions for the development of secure audio encryption systems.