Hiding the Type of Skin Texture in Mice based on Fuzzy Clustering Technique

• Main Authors: Alaa Noori Mazhar, Ekhlas Falih
• Format: Article
• Language: Arabic
• Published: College of Science for Women, University of Baghdad 2020-09-01
• Series: Baghdad Science Journal
• Subjects: C-Mean, Extracting, LSB, Information hiding, Steganography
• Online Access: http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/3294
• ISSN: 2078-8665; 2411-7986

A substantial matter to confidential messages' interchange through the internet is transmission of information safely. For example, digital products' consumers and producers are keen for knowing those products are genuine and must be distinguished from worthless products. Encryption's science can be defined as the technique to embed the data in an images file, audio or videos in a style which should be met the safety requirements. Steganography is a portion of data concealment science that aiming to be reached a coveted security scale in the interchange of private not clear commercial and military data. This research offers a novel technique for steganography based on hiding data inside the clusters that resulted from fuzzy clustering. The approach has been employed to use Fuzzy C-Mean clustering (FCM) to find the robust image regions for hiding the type of skin texture features in mice. The steganography was implemented using Least Significant Bit (LSB) method.