Novel hybrid classifier based on fuzzy type-III decision maker and ensemble deep learning model and improved chaos game optimization
This paper presents a unique hybrid classifier that combines deep neural networks with a
type-III fuzzy system for decision-making. The ensemble incorporates ResNet-18, Efficient …
type-III fuzzy system for decision-making. The ensemble incorporates ResNet-18, Efficient …
FASNet: Federated Adversarial Siamese Networks for Robust Malware Image Classification
Malware detection faces considerable challenges due to the ever-evolving and complex
nature of cyber threats. Various deep learning models have demonstrated effectiveness in …
nature of cyber threats. Various deep learning models have demonstrated effectiveness in …
An Efficient Malware Detection Approach Based on Machine Learning Feature Influence Techniques for Resource-Constrained Devices
The growing use of computer resources in modern society makes it extremely vulnerable to
several cyber-attacks, including unauthorized access to equipment and computer systems' …
several cyber-attacks, including unauthorized access to equipment and computer systems' …
Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models
In the evolving cyber threat landscape, one of the most visible and pernicious challenges is
malware activity detection and analysis. Traditional detection and analysis methods face …
malware activity detection and analysis. Traditional detection and analysis methods face …
MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
AH Haque, LI Jahin, SYH Katib, SM Tuhee, M Tasnia - 2024 - dspace.bracu.ac.bd
Just as the digital transformation of everything in this 'Information Age'has acted substantially
to mitigate conventional crimes to a degree, the rate of cyber crime has parallelly elevated …
to mitigate conventional crimes to a degree, the rate of cyber crime has parallelly elevated …
[引用][C] Malware Identification Using CNN and Deep Forest with Transfer Learning
N Wahane, C Kumar - 2016