Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks - Publikacja - MOST Wiedzy

Twoje konto

zaloguj

Wyszukiwarka

Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks

Abstrakt

This paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to their predecessors. Despite the advances made, further improvements are desired to achieve even better performance in this field. The conducted experiments provide insights into how each modification affects the classification accuracy of the architectures, which is a measure of their ability to distinguish between stego and cover images. Based on the obtained results, potential enhancements are identified that future CNN designs could adopt to achieve higher accuracy while minimizing their complexity compared to current architectures. The impact of modifications on each model’s performance has been found to vary depending on the tested architecture and the steganography embedding method used.

Cytowania

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Autorzy (2)

Cytuj jako

Pełna treść

pełna treść publikacji nie jest dostępna w portalu

Słowa kluczowe

Informacje szczegółowe

Kategoria:
Aktywność konferencyjna
Typ:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Język:
angielski
Rok wydania:
2024
Opis bibliograficzny:
Martyniak R., Czaplewski B.: Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks// / : , 2024,
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1007/978-3-031-63751-3_4
Źródła finansowania:
  • Działalność statutowa/subwencja
Weryfikacja:
Politechnika Gdańska

wyświetlono 48 razy

Publikacje, które mogą cię zainteresować

An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key

2019

A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification

2022

Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation

2024

Selected Technical Issues of Deep Neural Networks for Image Classification Purposes

2019
Meta Tagi