Adaptive Dynamic Steganography Algorithm for Secure and Efficient Data Hiding

Abstract: The rapid growth of digital communication has increased the need for secure methods to protect sensitive information. Steganography conceals secret information within a seemingly normal cover medium, but conventional techniques often use fixed embedding strategies that may not suit different secret-data types and security requirements. This paper proposes an Adaptive Dynamic Steganography Algorithm that selects an appropriate data-hiding strategy according to secret-data characteristics, sensitivity, required security level, and cover-medium properties. The approach analyzes input conditions at runtime and selects suitable parameters to balance security, embedding capacity, imperceptibility, and computational efficiency. It aims to reduce unnecessary distortion for low-risk data while providing stronger protection for highly sensitive information. The framework can be evaluated using embedding capacity, imperceptibility, security, computational complexity, and resistance to steganalysis.

Keywords: Adaptive dynamic steganography, RASACA, machine learning, artificial intelligence, data hiding, information security