NDLI: Evolving GA Classifier for Breaking the Steganographic Utilities: Stools, Steganos and Jsteg

Content Provider	IEEE Xplore Digital Library
Author	Geetha, S. Sivatha Sindhu, S.S. Kamaraj, N.
Copyright Year	2007
Description	Author affiliation: Thiagarajar Coll. of Eng., Madurai (Geetha, S.; Sivatha Sindhu, S.S.)
Abstract	Differentiating anomalous image documents (stego image) from pure image file (cover image) is difficult and tedious. Steganalytic techniques strive to detect whether an image contains a hidden message or not. This paper presents a genetic algorithm (GA) based approach to image steganalysis. The basic idea is that, the various image quality metrics calculated on cover image files and on stego-image files vis-a-vis their denoised versions, are statistically different. GA is employed to derive a set of classification rules from image data using these image quality metrics and the support-confidence framework is utilized as fitness function to judge the quality of each rule. The generated rules are then used to detect or classify the image documents in a real-time environment. Unlike most existing GA-based approaches, because of the simple representation of rules and the effective fitness function, the proposed method is easier to implement while providing the flexibility to generally detect any new steganography technique. The implementation of the GA based image steganalyzer relies on the choice of these image quality metrics and the construction of a two-class classifier, which will discriminate between the adulterated and the untouched image samples. Experimental results show that the proposed technique provides promising detection rates.
Starting Page	230
Ending Page	234
File Size	276689
Page Count	5
File Format	PDF
ISBN	0769530508
DOI	10.1109/ICCIMA.2007.310
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-13
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Steganography Image quality Educational institutions Genetic algorithms Artificial neural networks Fuzzy logic Digital images Computational intelligence Information technology Counting circuits
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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