A survey of the recent trends in deep learning based malware detection

UH Tayyab, FB Khan, MH Durad, A Khan… - Journal of Cybersecurity …, 2022 - mdpi.com
Monitoring Indicators of Compromise (IOC) leads to malware detection for identifying
malicious activity. Malicious activities potentially lead to a system breach or data …

An efficient densenet-based deep learning model for malware detection

J Hemalatha, SA Roseline, S Geetha, S Kadry… - Entropy, 2021 - mdpi.com
Recently, there has been a huge rise in malware growth, which creates a significant security
threat to organizations and individuals. Despite the incessant efforts of cybersecurity …

A new malware classification framework based on deep learning algorithms

Ö Aslan, AA Yilmaz - Ieee Access, 2021 - ieeexplore.ieee.org
Recent technological developments in computer systems transfer human life from real to
virtual environments. Covid-19 disease has accelerated this process. Cyber criminals' …

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 …

A comprehensive survey of tools and techniques mitigating computer and mobile malware attacks

SA Roseline, S Geetha - Computers & Electrical Engineering, 2021 - Elsevier
In this era of modernization, digital technology plays a major role in all facets of life. We are
accustomed to using computers and smartphones to access information, create, express …

A novel detection and multi-classification approach for IoT-malware using random forest voting of fine-tuning convolutional neural networks

SB Atitallah, M Driss, I Almomani - Sensors, 2022 - mdpi.com
The Internet of Things (IoT) is prone to malware assaults due to its simple installation and
autonomous operating qualities. IoT devices have become the most tempting targets of …

FedMicro-IDA: A federated learning and microservices-based framework for IoT data analytics

SB Atitallah, M Driss, HB Ghezala - Internet of Things, 2023 - Elsevier
Abstract The Internet of Things (IoT) has recently proliferated in both size and complexity.
Using multi-source and heterogeneous IoT data aids in providing efficient data analytics for …

Visualized malware multi-classification framework using fine-tuned CNN-based transfer learning models

W El-Shafai, I Almomani, A AlKhayer - Applied Sciences, 2021 - mdpi.com
There is a massive growth in malicious software (Malware) development, which causes
substantial security threats to individuals and organizations. Cybersecurity researchers …

Quantum Mayfly optimization with encoder-decoder driven LSTM networks for malware detection and classification model

OA Alzubi, JA Alzubi, TM Alzubi, A Singh - Mobile Networks and …, 2023 - Springer
Malware refers to malicious software developed to penetrate or damage a computer system
without any owner's informed consent. It uses target system susceptibilities, like bugs in …

Analyzing machine learning approaches for online malware detection in cloud

JC Kimmell, M Abdelsalam… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
The variety of services and functionality offered by various cloud service providers (CSP)
have exploded lately. Utilizing such services has created numerous opportunities for …