An Efficient and Secure Multi-Layered Image Steganography Approach Using LSB and Lightweight XOR Encryption for Improving Time and Space Complexity

Steganography is the practice of hiding information within another data in such a way that the presence of the hidden message is undetectable to causal observers. Encryption which makes data unreadable without a decrypt key, Steganography conceals the very existence of the data. In steganography, data is embedded within a carrier medium such as Image, Audio files, video files, Text files, Network protocols. But most popular among them is Image. For hiding secret information there exist a large variety of stenographic technique some are more complex than others and all of them have respective strong and weak points. Steganalysis, the detection of this hidden information, is an inherently difficult problem and requires a thorough investigation. So we are using LSB algorithm. Beside Complex encoding in steganography we are also focus on time and space complexity because if we only make complex encoding in steganography then file size will increase and it will be a problem for file transfer and downloading. This research presents a cutting-edge image steganography method that effectively and securely conceals data by combining Least Significant Bit (LSB) embedding with XOR-based lightweight encryption for maintaining Time and space complexity. The technique increases resistance to unwanted extraction by randomly distributing encrypted messages throughout the image using password-driven pixel randomization. A unique psychological component is included: users are presented with the statement, “Hidden Message will not get revealed,” during their first attempt at decoding, which intentionally builds suspense and discourages inadvertent intrusions. The hidden content, which may be displayed in mirrored format to further obfuscate it, is revealed through subsequent interactions. Simple encoding and decoding procedures are made possible by the intuitive interface, which was created with Google Colab’s ipywidgets. The method’s feasibility for safe image-based information concealment is confirmed by experimental evaluations that show good fidelity with little distortion.