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Image steganography and steganalysis
Author(s) -
Bachrach Mayra,
Shih Frank Y.
Publication year - 2011
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.152
Subject(s) - steganalysis , steganography , steganography tools , computer science , artificial intelligence , digital image , information hiding , key (lock) , image (mathematics) , least significant bit , the internet , pattern recognition (psychology) , data mining , computer vision , computer security , image processing , world wide web , operating system
Image steganography is used to embed covert messages in the form of files, text, or other images in digital images. The intent is to transmit hidden information. Steganalysis is the process used to detect hidden messages in images. Although steganography is not a new discipline, it has become increasingly important in today's digital world where information is often and easily exchanged through the Internet, email, and other means using computers. The need for better methods and techniques which can be used both to embed hidden information in images and to detect messages hidden in images is driving new research in the area of steganography and steganalysis. This article surveys image steganography and steganalysis. The aim is to introduce the uninformed reader to image steganography and steganalysis. The key concepts behind image steganography and steganalysis are explained. The history and origin of steganography are outlined. Steganography is compared with watermarking in technique and intent. Details of how images are represented are explained. Methods and algorithms used to embed messages in images and to detect embedded messages are explored. Currently available steganography and steganalysis tools are explained. A demonstration of how to embed hidden information in an image using available steganography tools is provided. WIREs Comp Stat 2011 3 251–259 DOI: 10.1002/wics.152 This article is categorized under: Data: Types and Structure > Image and Spatial Data