Steganalisis Blind dengan Metode Convolutional Neural Network (CNN) Yedroudj- Net terhadap Tools Steganografi

Penulis

Nurmi Hidayasari, Imam Riadi, Yudi Prayudi

Abstrak

Steganalisis digunakan untuk mendeteksi ada atau tidaknya file steganografi. Salah satu kategori steganalisis adalah blind steganalisis, yaitu cara untuk mendeteksi file rahasia tanpa mengetahui metode steganografi apa yang digunakan. Sebuah penelitian mengusulkan bahwa metode Convolutional Neural Networks (CNN) dapat mendeteksi file steganografi menggunakan metode terbaru dengan nilai probabilitas kesalahan rendah dibandingkan metode lain, yaitu CNN Yedroudj-net. Sebagai metode steganalisis Machine Learning terbaru, diperlukan eksperimen untuk mengetahui apakah Yedroudj-net dapat menjadi steganalisis untuk keluaran dari tools steganografi yang biasa digunakan. Mengetahui kinerja CNN Yedroudj-net sangat penting, untuk mengukur tingkat kemampuannya dalam hal steganalisis dari beberapa tools. Apalagi sejauh ini, kinerja Machine Learning masih diragukan dalam blind steganalisis. Ditambah beberapa penelitian sebelumnya hanya berfokus pada metode tertentu untuk membuktikan kinerja teknik yang diusulkan, termasuk Yedroudj-net. Penelitian ini akan menggunakan lima alat yang cukup baik dalam hal steganografi, yaitu Hide In Picture (HIP), OpenStego, SilentEye, Steg dan S-Tools, yang tidak diketahui secara pasti metode steganografi apa yang digunakan pada alat tersebut. Metode Yedroudj-net akan diimplementasikan dalam file steganografi dari output lima alat. Kemudian perbandingan dengan tools steganalisis lain, yaitu StegSpy. Hasil penelitian menunjukkan bahwa Yedroudj-net bisa mendeteksi keberadaan file steganografi. Namun, jika dibandingkan dengan StegSpy hasil gambar yang tidak terdeteksi lebih tinggi.


Abstract

Steganalysis is used to detect the presence or absence of steganograpy files. One category of steganalysis is blind steganalysis, which is a way to detect secret files without knowing what steganography method is used. A study proposes that the Convolutional Neural Networks (CNN) method can detect steganographic files using the latest method with a low error probability value compared to other methods, namely CNN Yedroudj-net. As the latest Machine Learning steganalysis method, an experiment is needed to find out whether Yedroudj-net can be a steganalysis for the output of commonly used steganography tools. Knowing the performance of CNN Yedroudj-net is very important, to measure the level of ability in terms of steganalysis from several tools. Especially so far, Machine Learning performance is still doubtful in blind steganalysis. Plus some previous research only focused on certain methods to prove the performance of the proposed technique, including Yedroudj-net. This research will use five tools that are good enough in terms of steganography, namely Hide In Picture (HIP), OpenStego, SilentEye, Steg and S-Tools, which is not known exactly what steganography methods are used on the tool. The Yedroudj-net method will be implemented in a steganographic file from the output of five tools. Then compare with other steganalysis tools, namely StegSpy. The results showed that Yedroudj-net could detect the presence of steganographic files. However, when compared with StegSpy the results of undetected images are higher.

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Referensi


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DOI: http://dx.doi.org/10.25126/jtiik.2020703326