AI-Enhanced LSB Steganography Interface: Concealed Data Embedding Framework

Steganography involves concealing text-based secret data within non-text files such as image, audio, or video files, with the extraction of the hidden data taking place at its destination. This avoids detection. Therefore, it becomes challenging for anyone to detect the presence of a concealed message within the image, highlighting the increasing importance of data privacy in contemporary times. The primary objective of Steganography is to enable clandestine communication between two individuals, typically involving the processes of encoding and decoding. This project specifically focuses on image Steganography, allowing the encoding and decoding of data within an image file. Through the utilization of steganography, an individual can conceal a substantial amount of text, comprising thousands of words, within a standard-sized image. To implement this Steganography approach, Python Image Library (PIL) is employed in conjunction with the Tkinter framework. LSB (Least Significant Bit) steganography techniques are applied for encryption and decryption functionalities. The primary goal is to create an application that employs LSB insertion to encode data within a cover image and, in a user-friendly manner, decode the original message from the embedded image. Additionally, AI-based encryption methodologies are integrated to enhance data security and fortify the concealment of information within the images, showcasing the synergy between advanced encryption techniques and traditional steganographic methods.