Medikal Görüntülerde Derin Öğrenme ile Steganaliz

Yıl 2021, Cilt: 14 Sayı: 2, 151 - 159, 30.04.2021

Rukiye Karakış , Kali Gurkahraman

https://doi.org/10.17671/gazibtd.799370

Cited By: 1

Öz

Steganaliz ile bir medya dosyasındaki gizli mesajı elde etmek ya da sadece mesajın varlığını tespit etmek amaçlanır. Literatürde medikal verilerin güvenliğini sağlamayı amaçlayan pek çok steganografi yöntemi mevcut olsa da medikal steganaliz çalışması çok azdır. Bu çalışmada, medikal görüntü steganografi yöntemlerinin dayanıklılığının arttırılmasında kullanılabilecek ve medikal bir görüntüde gizli mesajların varlığını tespit edebilecek bir sınıflandırıcı geliştirilmesi amaçlanmıştır. Bunun için karmaşık ve maliyetli öznitelik analizine gerek duymayan bir derin öğrenme mimarisi olan evrişimsel sinir ağı(ESA) taşıyıcı ve stego medikal görüntüler ile eğitilmiş ve test edilmiştir. Doğruluk, kesinlik, hassasiyet ve F1 değerleri sırasıyla 0,964, 0,966, 0965 ve 0964 olarak elde edilmiştir. Bu çalışma, derin öğrenme yönteminin medikal görüntü steganalizinde de kullanılabileceğini ilk kez göstermiştir.

Anahtar Kelimeler

derin öğrenme, evrişimsel sinir ağı, medikal görüntü steganalizi, medikal görüntü steganografi, uzamsal düzlem

Steganalysis with Deep Learning on Medical Images

Öz

With steganalysis, it is aimed to obtain a hidden message from a media file or only to detect the presence of the message. Although there are many steganography methods in the literature aiming to ensure the medical data security, medical steganalysis studies are very few. In this study, it is aimed to develop a classifier that can be used to increase the durability of medical image steganography methods and detect the presence of hidden messages in a medical image. For this, the convolutional neural network (CNN), a deep learning architecture that does not require complex and costly feature analysis, has been trained and tested with cover and stego medical images. Accuracy, precision, recall and F1 values were obtained as 0.964, 0.966, 0965 and 0964, respectively. This study has shown for the first time that the deep learning method can also be used in medical image steganalysis.

Anahtar Kelimeler

deep learning, convolutional neural network, medical image steganalysis, medical image steganography, spatial transform

Kaynakça

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