Earticle

초록

영어

This work proposes two main contributions to statistical steganalysis of Yet Another Steganographic Scheme (YASS) in JPEG images. Firstly, this work presents a reliable blind steganalysis technique to predict YASS which is one of recent and least statistically detectable embedding scheme using only five features, four Huffman length statistics (H) and the ratio of file size to resolution (FR Index). Secondly these features are shown to be unique, accurate and monotonic over a wide range of settings for YASS and several supervised classifiers with the accuracy of prediction superior to most blind steganalyzers in vogue. Overall, the proposed model having Huffman Length Statistics as its linchpin predicts YASS with an average accuracy of over 94 percent.

목차

Abstract
 1. Introduction
 2. Related Works
 3. YASS – Yet Another Steganographic Scheme
 4. Feature Extraction – Huffman Length Statistics and FR Index
  4.1. Huffman Length Statistics
  4.2. FR Index: Ratio of File Size to Resolution of an Image
 5. Image Database
  5.1 Exploratory Data Analysis of the Image Database
  5.2 Hypotheses Testing in Attempt to Predict the Big Block Size Used.
 6. Implementation
  6.1. Model
  6.2. Classification
 7. Results and Performance Analyses
  7.1. Comparison of the Proposed Model Against Blind Steganalyzers Tested in YASS [6]
  7.2. Comparison of Our Proposed Model Against Blind Steganalyzers Used in EYASS [7].
  7.3. Comparison of Our Proposed Model Against Steganalytic Feature Sets Tested in [5].
  7.4. Comparison of Our Proposed Model Against Steganalytic Feature Sets Tested in [8].
 8. Conclusions and Future Work
 References

키워드

저자

• Veena H Bhat [ Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore, India, IBS-Bangalore, Bangalore, India. ]
• Krishna S [ Department of Electronics and Communication Engineering, University Visvesvaraya College of Engineering, Bangalore, India ]
• P Deepa Shenoy [ Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore, India ]
• Venugopal K R [ Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore, India ]
• L M Patnaik [ Vice Chancellor, Defence Institute of Advanced Technology, Pune, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605