A novel deep learning-based approach for malware detection

K Shaukat, S Luo, V Varadharajan - Engineering Applications of Artificial …, 2023 - Elsevier
Malware detection approaches can be classified into two classes, including static analysis
and dynamic analysis. Conventional approaches of the two classes have their respective …

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' …

[HTML][HTML] A novel machine learning approach for detecting first-time-appeared malware

K Shaukat, S Luo, V Varadharajan - Engineering Applications of Artificial …, 2024 - Elsevier
Conventional malware detection approaches have the overhead of feature extraction, the
requirement of domain experts, and are time-consuming and resource-intensive. Learning …

MCFT-CNN: Malware classification with fine-tune convolution neural networks using traditional and transfer learning in Internet of Things

S Kumar - Future Generation Computer Systems, 2021 - Elsevier
With ever-increasing, internet-connected devices provide an opportunity to fulfil the
attacker's malicious intention. They use malicious programs to compromise the devices and …

Intelligent vision-based malware detection and classification using deep random forest paradigm

SA Roseline, S Geetha, S Kadry, Y Nam - IEEE Access, 2020 - ieeexplore.ieee.org
Malware is a rapidly increasing menace to modern computing. Malware authors continually
incorporate various sophisticated features like code obfuscations to create malware variants …

Improving malicious email detection through novel designated deep-learning architectures utilizing entire email

T Muralidharan, N Nissim - Neural Networks, 2023 - Elsevier
In today's email dependent world, cyber criminals often target organizations using a variety
of social engineering techniques and specially crafted malicious emails. When successful …

Resnext+: Attention mechanisms based on resnext for malware detection and classification

Y He, X Kang, Q Yan, E Li - IEEE Transactions on Information …, 2023 - ieeexplore.ieee.org
Malware detection and classification are crucial for protecting digital devices and information
systems. Accurate identification of malware enables researchers and incident responders to …

Malware‐SMELL: A zero‐shot learning strategy for detecting zero‐day vulnerabilities

PH Barros, ETC Chagas, LB Oliveira, F Queiroz… - Computers & …, 2022 - Elsevier
One of the most relevant security problems is inferring whether a program has malicious
intent (malware software). Even though Antivirus is one of the most popular approaches for …

ConRec: malware classification using convolutional recurrence

A Mallik, A Khetarpal, S Kumar - Journal of Computer Virology and …, 2022 - Springer
Today, the extensive reliae on technology has exposed us to a constant threat of
sophisticated malware attacks. Various automated malware production techniques have …