NDLI: Cost-sensitive steganalysis with stochastic sensitvity and cost sensitive training error

Content Provider	IEEE Xplore Digital Library
Author	Zhi-Min He
Copyright Year	2012
Description	Author affiliation: Machine Learning and Cybernetic Research Center, School of Computer Science and Engineering, South China University of Technology, Guangzhou, China (Zhi-Min He)
Abstract	Steganalysis is a popular technology to determine whether there is hidden message embedded in the image. In the real application, misclassifying a stego image as a clean image is usually more costly than misclassifying a clean image as a stego image. In the current researches, few people realize this important point. In this paper, we train a cost-sensitive Radial Basis Function Neural Network (RBFNN) for steganalysis to improve the performance of steganalysis when the costs of misclassifications are different. We also propose a simple Cost-Sensitive Localized Generalization Error Model (CS-LGEM) to select a proper number of hidden neurons for RBFNN. The training error in the L-GEM is replaced by a cost sensitive training error. The experimental results show that the average cost of the proposed method is much lower than the standard RBFNN and the Support Vector Machine (SVM) which is adopted in many steganalysis methods.
Starting Page	349
Ending Page	354
File Size	854893
Page Count	6
File Format	PDF
ISBN	9781467314848
ISSN	2160133X
e-ISBN	9781467314879
DOI	10.1109/ICMLC.2012.6358938
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Abstracts Neurons Cost-Sensitive Steganalysis CS-LGEM
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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