Sensitivity of deep learning applied to spatial image steganalysis

Sensitivity of deep learning applied to spatial image steganalysis

In recent years, the traditional approach to spatial image steganalysis has shifted to deep learning (DL) techniques, which have improved the detection accuracy while combining feature extraction and classification in a single model, usually a convolutional neural network (CNN). The main contributio...

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Bibliographic Details
Main Authors: Reinel Tabares-Soto, Harold Brayan Arteaga-Arteaga, Alejandro Mora-Rubio, Mario Alejandro Bravo-Ortíz, Daniel Arias-Garzón, Jesús Alejandro Alzate-Grisales, Simon Orozco-Arias, Gustavo Isaza, Raúl Ramos-Pollán
Format: Article
Language:English
Published: PeerJ Inc. 2021-08-01
Series:PeerJ Computer Science
Subjects:
Convolutional neural network
Deep learning
Steganalysis
Steganography
Sensitivity
Online Access:https://peerj.com/articles/cs-616.pdf

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https://peerj.com/articles/cs-616.pdf

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