most citedUnsupervised Steganalysis Based on Artificial Training Sets

75 citations · 116 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CR2019

Detection of Classifier Inconsistencies in Image Steganalysis

Daniel Lerch-Hostalot, David Megías

In this paper, a methodology to detect inconsistencies in classification-based image steganalysis is presented. The proposed approach uses two classifiers: the usual one, trained w…

cs.CR201721 cited

PSUM:Peer-to-peer multimedia content distribution using collusion-resistant fingerprinting

Amna Qureshi, David Megías, Helena Rifà-Pous

The use of peer-to-peer (P2P) networks for multimedia distribution has spread out globally in recent years. The mass popularity is primarily driven by cost-effective distribution o…

cs.CR201720 cited

Collusion-resistant and privacy-preserving P2P multimedia distribution based on recombined fingerprinting

David Megías, Amna Qureshi

Recombined fingerprints have been suggested as a convenient approach to improve the efficiency of anonymous fingerprinting for the legal distribution of copyrighted multimedia cont…

cs.MM2017

LSB Matching Steganalysis Based on Patterns of Pixel Differences and Random Embedding

Daniel Lerch-Hostalot, David Megías

This paper presents a novel method for detection of LSB matching steganogra- phy in grayscale images. This method is based on the analysis of the differences between neighboring pi…

cs.MM201775 cited

Unsupervised Steganalysis Based on Artificial Training Sets

Daniel Lerch-Hostalot, David Megías

In this paper, an unsupervised steganalysis method that combines artificial training setsand supervised classification is proposed. We provide a formal framework for unsupervisedcl…