Improving Image steganalysis performance using a graph-based feature selection method
سال انتشار: 1395
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 540
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شناسه ملی سند علمی:
JR_ACSIJ-5-3_006
تاریخ نمایه سازی: 19 آبان 1397
چکیده مقاله:
Steganalysis is the skill of discovering the use of steganography algorithms within an image with low or no information regarding the steganography algorithm or/and its parameters. The highdimensionality of image data with small number of samples has presented a difficult challenge for the steganalysis task. Several methods have been presented to improve the steganalysis performance by feature selection. Feature selection, also known as variable selection, is one of the fundamental problems in thefields of machine learning, pattern recognition and statistics. The aim of feature selection is to reduce the dimensionality of image data in order to enhance the accuracy of Steganalysis task. In this paper, we have proposed a new graph-based blind steganalysis method for detecting stego images from the cover images in JPEG images using a feature selection technique based on community detection. The experimental results show that the proposed approach is easy to be employed for steganalysis purposes. Moreover, performance of proposed method is better than several recent and well-known feature selection-based Image steganalysis methods.
کلیدواژه ها:
نویسندگان
Amir Nouri
Islamic Azad University, Ashtian Branch, Faculty of Computer Engineering, Ashtian, Iran
Alimohammad Nazari
Department of Mathematics, Arak university, Arak, Iran, P.O. Box, ۳۸۱۵۶-۸-۸۳۴۹