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Improved detection and evaluation for JPEG steganalysis

Published: 19 October 2009 Publication History

Abstract

Detection of information-hiding in JPEG images is actively delivered in steganalysis community due to the fact that JPEG is a widely used compression standard and several steganographic systems have been designed for covert communication in JPEG images. In this paper, we propose a novel method of JPEG steganalysis. Based on an observation of bi-variate generalized Gaussian distribution in Discrete Cosine Transform (DCT) domain, neighboring joint density features on both intra-block and inter-block are extracted. Support Vector Machines (SVMs) are applied for detection. Experimental results indicate that this new method prominently improves a current art of steganalysis in detecting several steganographic systems in JPEG images. Our study also shows that it is more accurate to evaluate the detection performance in terms of both image complexity and information hiding ratio.

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  • (2020)A Review of Color Image Steganalysis in the Transform Domain2020 14th International Conference on Innovations in Information Technology (IIT)10.1109/IIT50501.2020.9299075(45-50)Online publication date: 17-Nov-2020
  • (2017)A Survey on Different Feature Extraction and Classification Techniques Used in Image SteganalysisJournal of Information Security10.4236/jis.2017.8301308:03(186-202)Online publication date: 2017
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cover image ACM Conferences
MM '09: Proceedings of the 17th ACM international conference on Multimedia
October 2009
1202 pages
ISBN:9781605586083
DOI:10.1145/1631272
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 19 October 2009

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Author Tags

  1. JPEG
  2. Markov
  3. SVM
  4. generalized gaussian distribution
  5. image complexity
  6. joint density
  7. steganalysis

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MM09
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MM09: ACM Multimedia Conference
October 19 - 24, 2009
Beijing, China

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all
  • (2020)Advantages and disadvantages of using cryptography in steganography2020 17th International ISC Conference on Information Security and Cryptology (ISCISC)10.1109/ISCISC51277.2020.9261921(88-94)Online publication date: 9-Sep-2020
  • (2020)A Review of Color Image Steganalysis in the Transform Domain2020 14th International Conference on Innovations in Information Technology (IIT)10.1109/IIT50501.2020.9299075(45-50)Online publication date: 17-Nov-2020
  • (2017)A Survey on Different Feature Extraction and Classification Techniques Used in Image SteganalysisJournal of Information Security10.4236/jis.2017.8301308:03(186-202)Online publication date: 2017
  • (2016)Steganalysis Over Large-Scale Social Networks With High-Order Joint Features and Clustering EnsemblesIEEE Transactions on Information Forensics and Security10.1109/TIFS.2015.249691011:2(344-357)Online publication date: Feb-2016
  • (2015)A method to detect AAC audio forgeryProceedings of the 8th International Conference on Mobile Multimedia Communications10.5555/2826112.2826155(198-204)Online publication date: 25-May-2015
  • (2015)Steganalysis of JPEG images using enhanced neighbouring joint density featuresIET Image Processing10.1049/iet-ipr.2013.08239:7(545-552)Online publication date: Jul-2015
  • (2015)FS-EHS: Harmony Search Based Feature Selection Algorithm for Steganalysis Using ELMInnovations in Bio-Inspired Computing and Applications10.1007/978-3-319-28031-8_34(393-402)Online publication date: 15-Dec-2015
  • (2015)Exposing Image Tampering with the Same Quantization MatrixMultimedia Data Mining and Analytics10.1007/978-3-319-14998-1_15(327-343)Online publication date: 1-Apr-2015
  • (2014)Improved Approaches with Calibrated Neighboring Joint Density to Steganalysis and Seam-Carved Forgery Detection in JPEG ImagesACM Transactions on Intelligent Systems and Technology10.1145/25603655:4(1-30)Online publication date: 29-Dec-2014
  • (2013)Steganalysis for JPEG Images Using Extreme Learning MachineProceedings of the 2013 IEEE International Conference on Systems, Man, and Cybernetics10.1109/SMC.2013.235(1361-1366)Online publication date: 13-Oct-2013
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