Adaptive Dynamic Steganography Algorithm for Secure and Efficient Data Hiding Using RACESA

Abstract: Steganography provides a means of concealing secret information within a cover medium while maintaining its perceptual quality and security. However, the use of a fixed embedding technique may not provide an appropriate balance between security, capacity, distortion, and computational requirements for different data-hiding scenarios. This paper proposes RACESA (Runtime-Adaptive Cover and Embedding Strategy Algorithm), a framework that dynamically selects a suitable cover medium, existing embedding strategy, and embedding parameters according to runtime requirements. The proposed approach considers secret-data characteristics, security requirements, payload capacity, allowable distortion, execution time, and memory limitations. Candidate configurations are filtered and evaluated using a multi-criteria selection mechanism, followed by embedding and constraint verification. If the selected configuration fails to satisfy the specified requirements, an alternative feasible configuration is considered. The proposed framework provides a flexible decision-making mechanism for adapting existing steganographic techniques to different application requirements.

Keywords: Steganography, Adaptive Steganography, Dynamic Data Hiding, Cover Selection, Embedding Strategy, Secure Data Hiding, RACESA.