Payload Enhancement on Least Significant Bit Image Steganography using Edge Area Dilation

This research proposes a method to enhance the payload message by embedding messages on the dilated edge areas by the Least Significant Bit (LSB) method. To add security aspects to messages, messages are not embedded directly on the LSB but encrypted with XOR operations with Most Significant Bit (MSB). The experimental results of the test in this study showed that the dilation process to some extent can increase the payload of 18.65% and the average bpp is 1.42 while maintaining the imperceptibilty quality of stego image with an average PSNR value of about 47 dB, SSIM is 0.9977 and MSE is 1.13

Payload Enhancement on Least Significant Bit Image Steganography using Edge Area Dilation

This research proposes a method to enhance the payload message by embedding messages on the dilated edge areas by the Least Significant Bit (LSB) method. To add security aspects to messages, messages are not embedded directly on the LSB but encrypted with XOR operations with Most Significant Bit (MSB). The experimental results of the test in this study showed that the dilation process to some extent can increase the payload of 18.65% and the average bpp is 1.42 while maintaining the imperceptibilty quality of stego image with an average PSNR value of about 47 dB, SSIM is 0.9977 and MSE is 1.13

Reversible difference expansion multi-layer data hiding technique for medical images

Maintaining the privacy and security of confidential information in data communication has always been a major concern. It is because the advancement of information technology is likely to be followed by an increase in cybercrime, such as illegal access to sensitive data. Several techniques were proposed to overcome that issue, for example, by hiding data in digital images. Reversible data hiding is an excellent approach for concealing private data due to its ability to be applied in various fields. However, it yields a limited payload and the quality of the image holding data (Stego image), and consequently, these two factors may not be addressed simultaneously. This paper addresses this problem by introducing a new non-complexity difference expansion (DE) and block-based reversible multi-layer data hiding technique constructed by exploring DE. Sensitive data are embedded into the difference values calculated between the original pixels in each block with relatively low complexity. To improve the payload capacity, confidential data are embedded in multiple layers of grayscale medical images while preserving their quality. The experiment results prove that the proposed technique has increased the payload with an average of 369999 bits and kept the peak signal to noise ratio (PSNR) to the average of 36.506 dB using medical images' adequate security the embedded private data. This proposed method has improved the performance, especially the secret size, without reducing much the quality. Therefore, it is suitable to use for relatively big payloads

Öngörü hatalarına dayalı tersinir görüntü damgalama yöntemlerinin karşılaştırılması

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Bu tezde, sayısal bir görüntüye uygulanan farklı iki tersinir görüntü damgalama algoritması kıyaslanmıştır. İlk algoritma, öngörü hatalarının genişletilmesine dayalı uyarlanır bir yöntemdir. Bu yöntem ile mevcut tersinir görüntü damgalama yöntemlerindeki gibi görüntüdeki tüm piksellere aynı damgalama algoritması uygulamak yerine öngörü hatalarının aldığı değerlere göre pikseller farklı iki şekilde damgalanmaktadır. Bu amaçla, görüntü pikselleri düzgün ve düzgün olmayan şekilde iki bloğa ayrılmıştır. Düzgün blokların belirli piksellerine 2-bit damgalama, düzgün olmayan blokların belirli piksellerine ise 1-bit damgalama uygulanarak damgalama kapasitesi arttırılmıştır. Ayrıca, yüksek bozunuma sebep olan pikseller belirlenip bu pikseller damgalamada kullanılmayarak damgalama sonucu orijinal görüntüde oluşan bozunum azaltılmıştır. İkinci algoritma, aradeğerleme hatalarının genişletilmesine dayalıdır. Yöntemde, aradeğerleme hatasından faydalanılmaktadır. Kıyaslanan iki yöntem ve literatürdeki mevcut yöntemler bilgisayar benzetimi ile karşılaştırılıp üstün ve zayıf olduğu yönler belirlenmiştir.In this thesis, two reversible image watermarking algorithms applied to a digital image are compared. The first algorithm is an adaptive method based on the extension of prediction errors. With this method, instead of applying the same watermarking algorithm to all pixels in the image as in the current reversible image watermarking methods, the pixel is embeded in two different ways according to the values received by the prediction errors. For this purpose, the image pixels are divided into two parts, such as "flat regions" and "rough regions". Watermarking capacity is increased by applying 2-bit swatermarking to specific pixels of flat blocks and 1-bit watermarking to specific pixels of rough blocks. In addition, distorting pixels are identified and these pixels are not used in the watermarking, resulting in reduced distortion occurring in the original image resulting from the watermarking. The second algorithm is based on the expansion of interpolation errors. In the method, the amount of additional information needed to extract the watermarked value and restore the original image are very small. The two comparative methods and the existing methods in the literature are compared with computer simulations and found to be superior and weak