<![CDATA[The rapid advancement of information and communication technology has increased the need for data security and confidentiality in digital information exchange. Various threats, such as eavesdropping, data theft, and information manipulation, require effective security methods capable of protecting message content without attracting unauthorized attention. One of the techniques used to address this issue is steganography, which conceals secret information within digital media so that the existence of the message remains undetectable. This study aims to implement the Least Significant Bit (LSB) method on digital facial images as a medium for embedding secret messages and to evaluate the quality of the resulting stego images. The system was developed using the Python programming language with a Tkinter-based graphical user interface to facilitate the processes of message embedding and extraction. Prior to embedding, the secret message was secured using an XOR encryption operation with a specific key. The embedding process was performed by modifying the least significant bits of image pixels, resulting in minimal visual distortion. Experimental results indicate that the LSB method successfully conceals secret messages while maintaining the visual quality of the cover image. The evaluation produced low Mean Squared Error (MSE) values and Peak Signal-to-Noise Ratio (PSNR) values exceeding 85 dB, indicating a very high similarity between the original and stego images. Furthermore, the hidden message could be accurately extracted using the correct key, provided that the image had not undergone compression or manipulation. Therefore, the LSB-based steganography approach on digital facial images is proven to be an effective method for enhancing information security and confidentiality.]]>
