Multi-Layered Password-Based Steganography: A Novel Approach for Tiered Information Hiding

Since the advent of the Internet, information security has emerged as one of the most crucial aspects of information technology and communication. Over the past decade, numerous image steganographic techniques have been developed, primarily concentrating on optimizing payload capacity and image quality. This paper introduces a multi-layered steganographic framework that overcomes these limitations through tiered AES-CBC encryption and independent key derivation for each layer, enabling granular access control. Leveraging the ALASKA2 dataset, our method embeds ciphertexts generated from distinct user passwords into cover images via least significant bit (LSB) steganography. Experimental results demonstrate that three-layer configurations achieve optimal security-performance trade-offs, supporting payloads up to 1780 KB while maintaining imperceptible distortion (PSNR >60 dB). Enhanced security is evidenced by rising statistical metrics (MSE: 0.0098, Chi-Square: 76.13 for three layers), reflecting resilience against steganalysis and bruteforce attacks. Notably, the framework’s layered architecture ensures that compromising one layer does not expose others—a critical advancement over single-layer methods. While payload capacity remains constrained, our approach provides a scalable solution for applications demanding tiered security, such as medical data sharing or confidential enterprise communications.