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Please use this identifier to cite or link to this item: http://hdl.handle.net/11129/4516

Title: Image Steganography by LSB Substitution and Optimal Key Permutation Using Genetic Algorithm
Authors: Ergün, Cem
Al-Dazdaae, Soran Khalid Abdulrahman
Eastern Mediterranean University, Faculty of Engineering, Dept. of Computer Engineering
Keywords: Image steganography
Image processing - Digital techniques
Computer Security--Data Security
Image Processing.
Data Security
Image Steganography
LSB Substitution
Genetic Algorithm
Cross Over
Mutation
Elitism Selection
Tournament Selection
Computer Engineering
Issue Date: 2017
Publisher: Eastern Mediterranean University (EMU) - Doğu Akdeniz Üniversitesi (DAÜ)
Citation: Al-Dazdaae, Soran Khalid Abdulrahman. (2017). Image Steganography by LSB Substitution and Optimal Key Permutation Using Genetic Algorithm. Thesis (M.S.), Eastern Mediterranean University, Institute of Graduate Studies and Research, Dept. of Computer Engineering, Famagusta: North Cyprus.
Abstract: Steganography is an important data-hiding technique in which information is secretly passed between a sender and a receiver. In image steganography, a secret-message is embedded into a cover-image to create a stego-image. Furthermore, least significant bit substitution (LSB) is the most common technique used in image steganography. In LSB, either all or some of the pixels in the last four bits are replaced with pixels/a bit of the secret-message. Adding to its security issue, this technique is rather inefficient as it often results in a low-quality stego-image due to the high Mean Square Error (MSE) between the cover and stego-images. Consequently, two methods have been proposed to improve the stego-image’s quality: the first method involves using a Genetic Algorithm to uncover the optimal key permutation for embedding, while the second method involves elitism selection. This study adds to these by proposing an innovative method aimed at improving the stego-image’s quality. The method proposed by this study is rooted in both LSB substitution and optimal key permutation by Genetic Algorithm. First, the secret-image and the cover-image are selected, the secret-image is then converted to blocks, which are then encrypted and subsequently shuffled so as to make the embedded secret message meaningless to anyone without the encryption key. The method uses a genetic algorithm to calculate the optimal key permutation to improve the stego-image’s quality during LSB substitution. Using the method it proposes, the study found that the stego-image quality was improved substantially following the embedding of the “tiff” secret-image in the following cover-images: Baboon, Lena, Barbara, and Pepper. The study also found that the proposed method significantly reduced the computational complexity in the genetic algorithm.
ÖZ: Steganografi istenilen veriyi gizli bir şekilde göndermeye yarayan veri gizleme ya da saklama tekniğidir. Görüntü steganografisinde, stego resmini elde etmek için gizlenecek resim kapak resmine gömülerek elde edilir. LSB en genel kullanılan görüntü steganografı tekniğidir. Bu teknik her piksel sondan dört bitin ya da bazılarının gizlenecek resmin bitleri ile değiştirilmesi ile olur ve genellikle düşük kaliteli bir stego görüntüsü elde edilir. Sonuç olarak daha kaliteli stego görüntüsü elde etmek için iki yöntem önerilmiştir. İlk yöntemde en doğru permitasyonu ortaya çıkarmak amacıyla eniyileme için tasarlanan (GA) kullanılmıştır, ve genetik algoritmanın içine elitik seçme yöntemi eklenerek algoritmanın yakınsaması hızı artırılmıştır. Bu çalışmamızda önerilen yöntemler GA destekli LSB yer değiştirme ve en iyi anahtar permutasyonudur. İlk olarak kapak ve gizlenecek resim seçimi yapılır sonra gizli resim küçük bloklara bölünür, saklanacak resim bitleri bu bloklara bölündükden sonra her bir blok şifrelenir, blok sıraları karıştırılır. Bu şekilde elinde anahtar olmayan kişinin gizlenmiş mesajı çözmesi mümkün olmaz. Önerilen yöntem ile stego resmin kalitesinin artırıldığı içine yerleştirilen dört ayrı tift formatlı (gizli) resimde ispatlanmıştır. Bunlar resim işleme deneylerinde sıkça kullanılan, Lena, babuan, barbaro ve pepper resimleridir.
Description: Master of Science in Computer Engineering. Thesis (M.S.)--Eastern Mediterranean University, Faculty of Engineering, Dept. of Computer Engineering, 2017. Supervisor: Asst. Prof. Dr. Cem Ergün
URI: http://hdl.handle.net/11129/4516
Appears in Collections:Theses (Master's and Ph.D) – Computer Engineering

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