Bailey, K, Condell, Joan and Curran, K (2003) Steganography in Images: An Overview. In: Irish Machine Vision and Image Processing Conference (IMVIP2003), University of Ulster, Coleraine. University of Ulster. 9 pp. [Conference contribution]
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This paper gives an overview of the steganography process and reviews different steganalysis methods for images. Steganography involves sending a message through some innocuous carrier, for example an image or an audio file, to a receiver while preventing anyone else from knowing that a message is being sent at all. Computer based steganography allows changes to be made to digital carriers e.g. an image. These changes represent the hidden message but result, if successful, in no discernible change to the carrier. In both cases the objective is not to make it difficult to read the message as cryptography does, but to hide the existence of the message in the first place. To investigate image-based steganography six common methods of steganography were implemented and their strengths and weaknesses were evaluated. To provide a common frame of reference, all of the steganography methods were implemented and analysed using GIF images. The methods were chosen for their different strengths in terms of resistance to different types of steganalysis or their ability to maximise the size of the message they could store. All of the methods used were based on the manipulation of the least significant bits of pixel values or the rearrangement of colours to create least significant bit or parity bit patterns that correspond to the message being hidden. The stegoed image inevitably suffered some distortion from the steganography process. In the case of manipulation of the least significant bits of pixel values there were strong indications of steganography in the palette also. Overall the colour rearrangement technique appears to be the most resistant to detection if suitable images are chosen. Techniques which attempt to maximise the message size they can store appear to be the least resistant to detection.
|Item Type:||Conference contribution (Paper)|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Intelligent Systems Research Centre
|Deposited By:||Dr Joan Condell|
|Deposited On:||19 Apr 2010 12:37|
|Last Modified:||19 Apr 2010 12:37|
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