A Study on Machine Learning for Steganalysis-Reference-Cited by-同舟云学术

A Study on Machine Learning for Steganalysis

Published:2019 Issue: Volume: Page:
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Container-title:Proceedings of the 3rd International Conference on Machine Learning and Soft Computing - ICMLSC 2019
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Author:

Jung Ki-Hyun¹

Affiliation:

1. Department of Cyber Security, Kyungil University, Gyeongsan, Gyeongbuk, Korea

Publisher

ACM Press

Reference14 articles.

1. Khan, A., Siddiqa, A., Munib, S., and Malik, S. A. 2014. A recent survey of reversible watermarking techniques, Information Sciences 279 (2014), 251--272.

2. Subhedar, M. S. and Mankar, V.H. 2014. Current status and key issues in image steganography: a survey, Computer Science Review 13 (2014), 95--113.

3. Nissar, A., Mir, A. H. (2010). Classification of steganalysis techniques: a study, Digital Signal Processing 20 (2010), 1758--1770.

4. Cho, S., Cha, B. H., Gawecki, M., and Kuo, C. C. 2013. Block-based image steganalysis: algorithm and performance evaluation, J. Vis. Commun. Image R. 24 (2013), 846--856.

5. Karampidis, K., Kavallieratour, E., and Papadourakis, G. 2018. A review of image steganalysis techniques for digital forensics. Journal of Information Security and Applications 40 (2018), 217--235.

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