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Enhancing Image Steganalysis with Adversarially Generated Examples

  • Kevin Alex ZhangEmail author
  • Kalyan Veeramachaneni
Conference paper
  • 571 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11527)

Abstract

The goal of image steganalysis is to counter steganography algorithms which attempt to hide a secret message within an image file. We focus specifically on blind image steganalysis in the spatial domain which involves detecting the presence of secret messages in image files without knowing the exact algorithm used to embed them. In this paper, we demonstrate that we can achieve better performance on the blind steganalysis task by training the YeNet architecture with adversarially generated examples provided by SteganoGAN.

Keywords

Steganalysis Steganography Deep learning 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.MITCambridgeUSA

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