Published May 31, 2021 | Version v1
Dataset Open

Sensitivity of deep learning applied to spatial image steganalysis dataset

Creators

  • 1. Department of Electronics and Automation, Universidad Autonoma de Manizales, Manizales, Caldas, Colombia
  • 2. Department of Computer Science, Universidad Autonoma de Manizales, Manizales, Caldas, Colombia
  • 3. Department of Systems and Informatics, Universidad de Caldas, Manizales, Caldas, Colombia
  • 4. Department of Systems Engineering, Universidad de Antioquia, Medellın, Antioquia, Colombia

Description

Dataset used on the paper "Sensitivity of deep learning applied to spatial image steganalysis", it comes from ”Break Our Steganographic System”: The Ins and Outs of Organizing BOSS from Patrick Bas, Tomas Filler, Tomas Pevny authorship , on the compress files cover.rar corresponds to cover images in pgm files, with the respective stego image from WOW and S-UNIWARD steganographic algoritms on Wow.rar and Suniward.rar respectively, and  Wownpy.rar and Suninpy.rar contained npy files of cover-stego images divided on Train, Test and Validation sets.

Files

Files (2.7 GB)

Name Size Download all
md5:3e033748509f96c8043ef94474f4f352
389.3 MB Download
md5:def3e1a5c2861506867b7be0148d093a
770.2 MB Download
md5:86b491ef9ee76435729e799c2786e839
392.2 MB Download
md5:07bca6322b62059303274410f1f4f368
391.4 MB Download
md5:77f374edd66a4cf8fa110f6b7666e240
768.3 MB Download

Additional details

References

  • Patrick Bas, Tomas Filler, Tomas Pevny. "Break Our Steganographic System": The Ins and Outs of Organizing BOSS. INFORMATION HIDING, May 2011, Czech Republic. pp.59-70, ff10.1007/978-3- 642-24178-9_15ff. ffhal-00648057f