Deep learning for steganalysis of diverse data types: A review of methods, taxonomy, challenges and future directions
Steganography and steganalysis are two interrelated aspects of the field of information
security. Steganography seeks to conceal communications, whereas steganalysis aims to …
security. Steganography seeks to conceal communications, whereas steganalysis aims to …
Deep learning for diverse data types steganalysis: A review
Steganography and steganalysis are two interrelated aspects of the field of information
security. Steganography seeks to conceal communications, whereas steganalysis is aimed …
security. Steganography seeks to conceal communications, whereas steganalysis is aimed …
ImageNet pre-trained CNNs for JPEG steganalysis
In this paper, we investigate pre-trained computer-vision deep architectures, such as the
EfficientNet, MixNet, and ResNet for steganalysis. These models pre-trained on ImageNet …
EfficientNet, MixNet, and ResNet for steganalysis. These models pre-trained on ImageNet …
How to pretrain for steganalysis
In this paper, we investigate the effect of pretraining CNNs on ImageNet on their
performance when refined for steganalysis of digital images. In many cases, it seems that …
performance when refined for steganalysis of digital images. In many cases, it seems that …
Towards faster vehicle routing by transferring knowledge from customer representation
The Vehicle Routing Problem (VRP) is a well-known NP-hard combinatorial optimization
problem, which has wide spread applications in real world, such as logistics, bus route …
problem, which has wide spread applications in real world, such as logistics, bus route …
Input feature mappings-based deep residual networks for fault diagnosis of rolling element bearing with complicated dataset
L Hou, R Jiang, Y Tan, J Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
Most rolling element bearing (REB) fault diagnosis algorithms are evaluated on the Case
Western Reserve University (CWRU) bearing dataset for its popularity and simplicity …
Western Reserve University (CWRU) bearing dataset for its popularity and simplicity …
Dataset mismatched steganalysis using subdomain adaptation with guiding feature
The generalization problem in deep learning has always been an important problem to be
solved. In the field of steganalysis, generalization is also an important factor that makes …
solved. In the field of steganalysis, generalization is also an important factor that makes …
An Ensemble Transfer Learning Model for Detecting Stego Images
As internet traffic grows daily, so does the need to protect it. Network security protects data
from unauthorized access and ensures their confidentiality and integrity. Steganography is …
from unauthorized access and ensures their confidentiality and integrity. Steganography is …
[PDF][PDF] A comprehensive tutorial and survey of applications of deep learning for cyber security
A Comprehensive Tutorial and Survey of Applications of Deep Learning for Cyber Security
Page 1 P osted on 5 Jan 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech rxiv.11473377.v1 …
Page 1 P osted on 5 Jan 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech rxiv.11473377.v1 …
Systemization of Knowledge (SoK)-Cross Impact of Transfer Learning in Cybersecurity: Offensive, Defensive and Threat Intelligence Perspectives
S Makar, A Dehghantanha, F Zarrinkalam… - arXiv preprint arXiv …, 2023 - arxiv.org
Recent literature highlights a significant cross-impact between transfer learning and
cybersecurity. Many studies have been conducted on using transfer learning to enhance …
cybersecurity. Many studies have been conducted on using transfer learning to enhance …