% This file was created with JabRef 2.3.1.
% Encoding: ANSI_X3.4-1968
+@inproceedings{DBLP:conf/apsipa/TanL14,
+ author = {Shunquan Tan and
+ Bin Li},
+ title = {Stacked convolutional auto-encoders for steganalysis of digital images},
+ booktitle = {Asia-Pacific Signal and Information Processing Association Annual
+ Summit and Conference, {APSIPA} 2014, Chiang Mai, Thailand, December
+ 9-12, 2014},
+ pages = {1--4},
+ year = {2014},
+ crossref = {DBLP:conf/apsipa/2014},
+ url = {http://dx.doi.org/10.1109/APSIPA.2014.7041565},
+ doi = {10.1109/APSIPA.2014.7041565},
+ timestamp = {Sat, 14 Mar 2015 17:34:07 +0100},
+ biburl = {http://dblp.uni-trier.de/rec/bib/conf/apsipa/TanL14},
+ bibsource = {dblp computer science bibliography, http://dblp.org}
+}
+@proceedings{DBLP:conf/apsipa/2014,
+ title = {Asia-Pacific Signal and Information Processing Association Annual
+ Summit and Conference, {APSIPA} 2014, Chiang Mai, Thailand, December
+ 9-12, 2014},
+ publisher = {{IEEE}},
+ year = {2014},
+ url = {http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7016284},
+ isbn = {978-6-1636-1823-8},
+ timestamp = {Sat, 14 Mar 2015 15:24:04 +0100},
+ biburl = {http://dblp.uni-trier.de/rec/bib/conf/apsipa/2014},
+ bibsource = {dblp computer science bibliography, http://dblp.org}
+}
+
+@inproceeding{doi:10.1117/12.2083479,
+author = {Qian, Yinlong and Dong, Jing and Wang, Wei and Tan, Tieniu},
+title = {
+Deep learning for steganalysis via convolutional neural networks
+},
+journal = {Proc. SPIE},
+volume = {9409},
+number = {},
+pages = {94090J-94090J-10},
+abstract = {
+Current work on steganalysis for digital images is focused on the construction of complex handcrafted features. This paper proposes a new paradigm for steganalysis to learn features automatically via deep learning models. We novelly propose a customized Convolutional Neural Network for steganalysis. The proposed model can capture the complex dependencies that are useful for steganalysis. Compared with existing schemes, this model can automatically learn feature representations with several convolutional layers. The feature extraction and classification steps are unified under a single architecture, which means the guidance of classification can be used during the feature extraction step. We demonstrate the effectiveness of the proposed model on three state-of-theart spatial domain steganographic algorithms - HUGO, WOW, and S-UNIWARD. Compared to the Spatial Rich Model (SRM), our model achieves comparable performance on BOSSbase and the realistic and large ImageNet database.
+},
+year = {2015},
+doi = {10.1117/12.2083479},
+URL = { http://dx.doi.org/10.1117/12.2083479},
+eprint = {}
+}
+
+
+
+@inproceedings{DBLP:conf/ijcai/CiresanMMGS11,
+ author = {Dan Claudiu Ciresan and
+ Ueli Meier and
+ Jonathan Masci and
+ Luca Maria Gambardella and
+ J{\"{u}}rgen Schmidhuber},
+ title = {Flexible, High Performance Convolutional Neural Networks for Image
+ Classification},
+ booktitle = {{IJCAI} 2011, Proceedings of the 22nd International Joint Conference
+ on Artificial Intelligence, Barcelona, Catalonia, Spain, July 16-22,
+ 2011},
+ pages = {1237--1242},
+ year = {2011},
+ crossref = {DBLP:conf/ijcai/2011},
+ url = {http://ijcai.org/papers11/Papers/IJCAI11-210.pdf},
+ timestamp = {Tue, 09 Aug 2011 14:09:58 +0200},
+ biburl = {http://dblp.uni-trier.de/rec/bib/conf/ijcai/CiresanMMGS11},
+ bibsource = {dblp computer science bibliography, http://dblp.org}
+}
+
+@proceedings{DBLP:conf/ijcai/2011,
+ editor = {Toby Walsh},
+ title = {{IJCAI} 2011, Proceedings of the 22nd International Joint Conference
+ on Artificial Intelligence, Barcelona, Catalonia, Spain, July 16-22,
+ 2011},
+ publisher = {{IJCAI/AAAI}},
+ year = {2011},
+ isbn = {978-1-57735-516-8},
+ timestamp = {Tue, 09 Aug 2011 14:09:58 +0200},
+ biburl = {http://dblp.uni-trier.de/rec/bib/conf/ijcai/2011},
+ bibsource = {dblp computer science bibliography, http://dblp.org}
+}
+
+
+@article{DBLP:journals/ftsig/DengY14,
+ author = {Li Deng and
+ Dong Yu},
+ title = {Deep Learning: Methods and Applications},
+ journal = {Foundations and Trends in Signal Processing},
+ volume = {7},
+ number = {3-4},
+ pages = {197--387},
+ year = {2014},
+ url = {http://dx.doi.org/10.1561/2000000039},
+ doi = {10.1561/2000000039},
+ timestamp = {Tue, 08 Jul 2014 15:28:41 +0200},
+ biburl = {http://dblp.uni-trier.de/rec/bib/journals/ftsig/DengY14},
+ bibsource = {dblp computer science bibliography, http://dblp.org}
+}
@article{BDCC16,
year={2015},
year = 2014
}
+@inproceedings{ccfg16:ip,
+author = {Jean-Fran\c{c}ois Couchot, Rapha\"el Couturier, Yousra Ahmed Fadil and Christophe Guyeux},
+title = {A Second Order Derivatives based Approach for Steganography},
+booktitle = {Secrypt 2016, 13th Int. Conf. on Security and Cryptography},
+pages = {***--***},
+address = {Lisbon},
+month = jul,
+year = 2014
+}
+
+
+
+Title:
+Authors:
+Abstract: Steganography schemes are designed with the objective of minimizing a defined distortion function. In most existing state of the art approaches, this distortion function is based on image feature preservation. Since smooth regions or clean edges define image core, even a small modification in these areas largely modifies image features and is thus easily detectable. On the contrary, textures, noisy or chaotic regions are so difficult to model that the features having been modified inside these areas are similar to the initial ones. These regions are characterized by disturbed level curves. This work presents a new distortion function for steganography that is based on second order derivatives, which are mathematical tools that usually evaluate level curves. Two methods are explained to compute these partial derivatives and have been completely implemented. The first experiments show that these approaches are promising.
year = 2014,
}
+@article{Robinson:1981:CS,
+ author = {Robinson, John P. and Cohn, Martin},
+ title = {Counting Sequences},
+ journal = {IEEE Trans. Comput.},
+ issue_date = {January 1981},
+ volume = {30},
+ number = {1},
+ month = jan,
+ year = {1981},
+ issn = {0018-9340},
+ pages = {17--23},
+ numpages = {7},
+ url = {http://dl.acm.org/citation.cfm?id=1963620.1963622},
+ acmid = {1963622},
+ publisher = {IEEE Computer Society},
+ address = {Washington, DC, USA},
+ keywords = {circuit testing, counters, gray codes, hamming distance, transition counts, uniform distance},
+}
+@article{DBLP:journals/combinatorics/BhatS96,
+ author = {Girish S. Bhat and
+ Carla D. Savage},
+ title = {Balanced Gray Codes},
+ journal = {Electr. J. Comb.},
+ volume = {3},
+ number = {1},
+ year = {1996},
+ url = {http://www.combinatorics.org/Volume_3/Abstracts/v3i1r25.html},
+ timestamp = {Tue, 05 Oct 2004 14:51:02 +0200},
+ biburl = {http://dblp.uni-trier.de/rec/bib/journals/combinatorics/BhatS96},
+ bibsource = {dblp computer science bibliography, http://dblp.org}
+}
\ No newline at end of file
