The New Development of Steganography Technique for Problem Solving of Gaussian Blur

Cybercrimes are increasingly invading the privacy of individuals, organizations, and governments. Personal data is increasingly insecure because of illegal data collected by unauthorized person. This study aims to develop a data embedding technique in image whose data robustness is tested when attacked by Gaussian Blur. The development of this technique uses the python programming language and the LSB (Least Significant Bit) method. By testing the gaussian blur attack using imperceptibility, fidelity, and robustness tests. The test results that have been carried out for imperceptibility testing use 25 respondents with 10 images and get a 80 percentage. The results of the fidelity test using 10 images found that an average MSE value is 0.001623 and an average PSNR value is 77.642 dB. The results of the robustness test using a blur radius of 0 to 1 on 10 stego-images obtained the message that 8 out of 10 stego-images could be extracted.