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Image Steganalysis Based on Wavelet Transformation
Abstract:
Techniques for information hiding have become increasingly more ophisticated and widespread. Steganalysis has recently received a great deal of attention both from law enforcement and the media. Attacks and analysis on hidden information may take several forms: detecting, extracting, and disabling or destroying hidden information. This paper provides wavelet based approach for image Steganalysis. The detection scheme of the system can be separated in two parts. In the first part, extraction a set of statistics, called the feature vector, for the investigated image. The second part, using a classification algorithm to separate original images from stego images by means of their feature vectors.
Keywords:
Image steganalysis, Wavelet, Statistical parameters, steganography, information hiding. Introduction: In today’s digital world, much more versatile and practical covers for hiding messages digital documents, images, video, and audio files have replaced invisible ink and paper. As long as an electronic document contains perceptually irrelevant or redundant information, it can be used as a “cover” to hide secret messages. Information hiding is a recently developed technique in the information security field and has received significant attention from both industry and academia. There are two main branches for information hiding–steganography and digital watermarking. The main purpose of steganography is to convey messages secretly by concealing the very existence of messages, while digital watermarking is mainly used for copyright protection of electronic product [1].
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- Image steganalysis, Wavelet, Statistical parameters, steganography, information hiding
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