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Implementasi invisible steganography via generative adverserial network (ISGAN) untuk steganografi gambar

Santi Indarjani - Personal Name; Sri Rosdiana - Personal Name; Sepha Siswantyo - Personal Name; Salsabila Hadida Difanda - Personal Name;

Abstrak:
Steganografi adalah salah satu teknik keamanan informasi yang bertujuan untuk menyembunyikan data atau pesan rahasia dalam berbagai media, seperti teks, gambar, audio, atau video. Banyak penelitian dan pembaruan telah dilakukan untuk meningkatkan kualitas dari steganografi gambar, salah satunya yaitu dengan menggunakan machine learning yang merupakan cabang dari Artificial Intelligence. Penelitian ini difokuskan pada implementasi steganografi menggunakan model machine learning Invisible Steganography via Generative Adversarial Network (ISGAN) pada gambar berwarna sebagai secret image dan cover image. Model ISGAN dipilih karena kemampuannya untuk menyembunyikan informasi secara tidak terlihat oleh mata manusia, yang secara signifikan meningkatkan keamanan dan privasi dalam pertukaran informasi. Sebelumnya, telah terdapat penelitian mengenai penggunaan ISGAN pada secret image greyscale dan cover image berwarna. Dalam penelitian ini dilakukan percobaan untuk mengevaluasi efektivitas penggunaan ISGAN pada gambar berwarna, baik pada secret maupun cover image. Hasil menunjukkan bahwa model ISGAN dapat diaplikasikan namun masih terdapat penurunan nilai PSNR dan SSIM yang mengindikasikan adanya perubahan yang dapat terdeteksi dalam kualitas gambar hasil steganografi.

Abstract:
Steganography is one of the information security techniques aimed at hiding secret data or messages in various media, such as text, images, audio, or video. Much research and development have been carried out to enhance the quality of image steganography, one of which is by using machine learning, a branch of Artificial Intelligence. This research is focused on implementing steganography using the Invisible Steganography via Generative Adversarial Network (ISGAN) machine learning model on color images as the secret image and cover image. The ISGAN model was chosen for its ability to hide information imperceptibly to the human eye, significantly enhancing security and privacy in information exchange. Previously, there has been research on the use of ISGAN on greyscale secret images and color cover images. This study conducts experiments to evaluate the effectiveness of using ISGAN on color images, both as secret and cover images. The results show that the ISGAN model can be applied, but there is still a decrease in PSNR and SSIM values, indicating detectable changes in the quality of the steganography result images.


Availability
#
Rekayasa Kriptografi 2023 SAL i
TA20230101846
Available - Read on Location
#
Rekayasa Kriptografi 2023 SAL i
TA20230101847
Available - Read on Location
Detail Information
Series Title
--
Call Number
2023 SAL i
Publisher
Bogor : Politeknik Siber dan Sandi Negara., 2023
Collation
xvi, 126 halaman
Language
Indonesia
ISBN/ISSN
--
Classification
Rekayasa Sistem Kriptografi
Content Type
-
Media Type
-
Carrier Type
-
Edition
--
Subject(s)
Artificial Intelligence
Machine learning
GAN
ISGAN
steganografi
Specific Detail Info
--
Statement of Responsibility
Salsabila Hadida Difanda
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