An Audio Steganography to Protect data in Text, Images and Audio with Hybrid Encryption Techniques

This research proposes an imaginative hybrid steganography technique meant to strengthen the protection of text, pictures, and audio in response to the critical problem of information security. The incorporation of strong encryption in audio steganography adds to the innovation. In response to rising dangers in digital communication, the study investigates the vulnerabilities of text, picture, and audio mediums. The inquiry looks into White Space and Least Significant Bit (LSB) approaches for text steganography, while Quantization Index Modulation (QIM) is combined with LSB for image steganography. A revolutionary hybrid solution for audio steganography develops, combining Adaptive QIM and LSB. Python implementations are provided to demonstrate the use and effectiveness of these strategies in maintaining data integrity and secrecy. The study broadens its reach by presenting a novel data security paradigm in audio files that combines AES encryption, Rubik’s Cube-like scrambling, and adaptive steganography. The method begins with strong AES encryption, which is then followed by a clever scrambling algorithm inspired by the Rubik’s Cube. The distinguishing characteristic is seen in the last stage, when adaptive QIM embeds scrambled data into audio files, thereby disguising encrypted material. This innovative solution not only strengthens data security through the complexities of AES and Rubik’s Cube-like scrambling, but it also pro- vides a full framework for safe data transfer, exemplifying the synergy of classical encryption and current steganography techniques. The results reveal a considerable improvement in information security across various digital forms, indicating a big step forward in reinforcing sensitive data transfer.