Image-based malware classification using VGG19 network and spatial convolutional attention

MJ Awan, OA Masood, MA Mohammed, A Yasin… - Electronics, 2021 - mdpi.com
In recent years the amount of malware spreading through the internet and infecting
computers and other communication devices has tremendously increased. To date …

Metamorphic malware and obfuscation: a survey of techniques, variants, and generation kits

K Brezinski, K Ferens - Security and Communication Networks, 2023 - Wiley Online Library
The competing landscape between malware authors and security analysts is an ever‐
changing battlefield over who can innovate over the other. While security analysts are …

A review of computer vision methods in network security

J Zhao, R Masood, S Seneviratne - … Communications Surveys & …, 2021 - ieeexplore.ieee.org
Network security has become an area of significant importance more than ever as
highlighted by the eye-opening numbers of data breaches, attacks on critical infrastructure …

Mitigating the risks of malware attacks with deep Learning techniques

AM Alnajim, S Habib, M Islam, R Albelaihi… - Electronics, 2023 - mdpi.com
Malware has become increasingly prevalent in recent years, endangering people,
businesses, and digital assets worldwide. Despite the numerous techniques and …

Task-Aware Meta Learning-Based Siamese Neural Network for Classifying Control Flow Obfuscated Malware

J Zhu, J Jang-Jaccard, A Singh, PA Watters… - Future Internet, 2023 - mdpi.com
Malware authors apply different techniques of control flow obfuscation, in order to create
new malware variants to avoid detection. Existing Siamese neural network (SNN)-based …

DeepAProt: Deep learning based abiotic stress protein sequence classification and identification tool in cereals

B Ahmed, MA Haque, MA Iquebal, S Jaiswal… - Frontiers in plant …, 2023 - frontiersin.org
The impact of climate change has been alarming for the crop growth. The extreme weather
conditions can stress the crops and reduce the yield of major crops belonging to Poaceae …

Attention‐based convolutional neural network deep learning approach for robust malware classification

V Ravi, M Alazab - Computational Intelligence, 2023 - Wiley Online Library
Recently, transforming windows files into images and its analysis using machine learning
and deep learning have been considered as a state‐of‐the art works for malware detection …

Deep learning framework and visualization for malware classification

S Akarsh, K Simran, P Poornachandran… - 2019 5th …, 2019 - ieeexplore.ieee.org
In this paper we propose a deep learning framework for classification of malware. There has
been an enormous increase in the volume of malware generated lately which represents a …

Detecting the presence of malware and identifying the type of cyber attack using deep learning and VGG-16 techniques

AIA Alzahrani, M Ayadi, MM Asiri, A Al-Rasheed… - Electronics, 2022 - mdpi.com
malware is malicious software (harmful program files) that targets and damage computers,
devices, networks, and servers. Many types of malware exist, including worms, viruses …

[PDF][PDF] A comprehensive tutorial and survey of applications of deep learning for cyber security

KP Soman, M Alazab, S Sriram - Authorea Preprints, 2023 - techrxiv.org
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 …