PENGEMBANGAN TEKNIK STEGANOGRAFI UNTUK MENGATASI PERMASALAHAN PADA GAUSSIAN BLUR
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Institusion
Universitas Teknokrat Indonesia
Author
PUTRI, CHINTYA VERONICA
Subject
Bahasa Pemrograman
Datestamp
2023-10-19 06:40:30
Abstract :
ABSTRAK Cybercrimes are increasingly invading the privacy of individuals, organizations and governments. Important personal data is increasingly insecure because of illegal data collection by people who have no interest in it. This study aims to develop a data embedding technique in images 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 percentage of 80%. The results of the fidelity test using 10 images by measuring the MSE value and PSNR value found that 10 images got an MSE value close to 0 or less than 1 and 10 images got a PSNR value of >40dB which can be said to be very good. The results of the robustness test using a blur radius of 0 to 1 on 10 images obtained the message that 8 out of 10 images could be extracted, so that overall this study was said to be "Successful and Very Good". Keywords : Steganography, Cybercrimes, LSB, Python Programming, Gaussian Blur
ABSTRAK Cybercrimes are increasingly invading the privacy of individuals, organizations and governments. Important personal data is increasingly insecure because of illegal data collection by people who have no interest in it. This study aims to develop a data embedding technique in images 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 percentage of 80%. The results of the fidelity test using 10 images by measuring the MSE value and PSNR value found that 10 images got an MSE value close to 0 or less than 1 and 10 images got a PSNR value of >40dB which can be said to be very good. The results of the robustness test using a blur radius of 0 to 1 on 10 images obtained the message that 8 out of 10 images could be extracted, so that overall this study was said to be "Successful and Very Good". Keywords : Steganography, Cybercrimes, LSB, Python Programming, Gaussian Blur
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