A survey on Deep-Learning-based image steganography

B Song, P Wei, S Wu, Y Lin, W Zhou - Expert Systems with Applications, 2024 - Elsevier
With the development of Internet and multimedia development, digital image steganography
is becoming more extensive in transmitting data with high capacity and security. Although …

Security and privacy issues in deep reinforcement learning: Threats and countermeasures

K Mo, P Ye, X Ren, S Wang, W Li, J Li - ACM Computing Surveys, 2024 - dl.acm.org
Deep Reinforcement Learning (DRL) is an essential subfield of Artificial Intelligence (AI),
where agents interact with environments to learn policies for solving complex tasks. In recent …

Enhance Software‐Defined Network Security with IoT for Strengthen the Encryption of Information Access Control

V Vimal, R Muruganantham, R Prabha… - Computational …, 2022 - Wiley Online Library
The Internet of Things (IoT) is legitimately growing quicker. The operators have already
started setting up a diligent infrastructure for these gadgets. Various technologies need to be …

Generative steganography via auto-generation of semantic object contours

Z Zhou, X Dong, R Meng, M Wang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
As a promising technique of resisting steganalysis detection, generative steganography
usually generates a new image driven by secret information as the stego-image. However, it …

Secret-to-image reversible transformation for generative steganography

Z Zhou, Y Su, J Li, K Yu, QMJ Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recently, generative steganography that transforms secret information to a generated image
has been a promising technique to resist steganalysis detection. However, due to the …

Image disentanglement autoencoder for steganography without embedding

X Liu, Z Ma, J Ma, J Zhang… - Proceedings of the …, 2022 - openaccess.thecvf.com
Conventional steganography approaches embed a secret message into a carrier for
concealed communication but are prone to attack by recent advanced steganalysis tools. In …

Steganography embedding cost learning with generative multi-adversarial network

D Huang, W Luo, M Liu, W Tang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Since the generative adversarial network (GAN) was proposed by Ian Goodfellow et al. in
2014, it has been widely used in various fields. However, there are only a few works related …

A multiwatermarking scheme for verifying medical image integrity and authenticity in the internet of medical things

F Yan, H Huang, X Yu - IEEE Transactions on Industrial …, 2022 - ieeexplore.ieee.org
With the advent of a fifth-generation mobile network and developments in technologies such
as the Internet of Medical Things, smart healthcare systems are becoming ubiquitous in our …

ReLOAD: Using reinforcement learning to optimize asymmetric distortion for additive steganography

X Mo, S Tan, W Tang, B Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, the success of non-additive steganography has demonstrated that asymmetric
distortion can remarkably improve security performance compared with symmetric cost …

StegaStyleGAN: towards generic and practical generative image steganography

W Su, J Ni, Y Sun - Proceedings of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
The recent advances in generative image steganography have drawn increasing attention
due to their potential for provable security and bulk embedding capacity. However, existing …