Ransomware classification and detection with machine learning algorithms

M Masum, MJH Faruk, H Shahriar… - 2022 IEEE 12th …, 2022 - ieeexplore.ieee.org
Malicious attacks, malware, and ransomware families pose critical security issues to
cybersecurity, and it may cause catastrophic damages to computer systems, data centers …

[HTML][HTML] MeMalDet: A memory analysis-based malware detection framework using deep autoencoders and stacked ensemble under temporal evaluations

P Maniriho, AN Mahmood, MJM Chowdhury - Computers & Security, 2024 - Elsevier
Malware attacks continue to evolve, making detection challenging for traditional static and
dynamic analysis techniques. On the other hand, memory analysis provides valuable …

[HTML][HTML] PDF malware detection based on optimizable decision trees

Q Abu Al-Haija, A Odeh, H Qattous - Electronics, 2022 - mdpi.com
Portable document format (PDF) files are one of the most universally used file types. This
has incentivized hackers to develop methods to use these normally innocent PDF files to …

A novel malware classification and augmentation model based on convolutional neural network

A Tekerek, MM Yapici - Computers & Security, 2022 - Elsevier
The rapid development and widespread use of the Internet have led to an increase in the
number and variety of malware proliferating via the Internet. Malware is the general …

Vehicle security: A survey of security issues and vulnerabilities, malware attacks and defenses

AA Elkhail, RUD Refat, R Habre, A Hafeez… - IEEE …, 2021 - ieeexplore.ieee.org
Recent years have led the path to the evolution of automotive technology and with these
new developments, modern vehicles are getting increasingly astute and offering growing …

A time-interval-based active learning framework for enhanced PE malware acquisition and detection

I Finder, E Sheetrit, N Nissim - Computers & Security, 2022 - Elsevier
Malware increasingly threatens users around the world on a variety of cybernetic platforms,
resulting in damages of billions of dollars each year. In recent years, in order to improve the …

Deep learning for windows malware analysis

M Belaoued, A Derhab, N Chekkai, C Ramdane… - … Malware: Offensive and …, 2023 - Springer
Malwares, such as ransomware, Trojans, spyware, and botnets, are the most common cyber-
threats that can cause significant damages for organizations, governments, and individuals …

Enhancing PDF Malware Detection through Logistic Model Trees.

M Binsawad - Computers, Materials & Continua, 2024 - search.ebscohost.com
Malware is an ever-present and dynamic threat to networks and computer systems in
cybersecurity, and because of its complexity and evasiveness, it is challenging to identify …

Ransomware classification using machine learning

NE Majd, T Mazumdar - 2023 32nd International Conference on …, 2023 - ieeexplore.ieee.org
The rise of ransomware has emerged as a pressing concern for the technology industry,
demanding prompt action to prevent monetary and ethical exploitation. Therefore, an …

Integrating a Rule-Based Approach to Malware Detection with an LSTM-Based Feature Selection Technique

S Bhardwaj, M Dave - SN Computer Science, 2023 - Springer
Technology has amplified malware activity, affecting network and users. Before being
forwarded to the next host, network traffic must be dynamically analysed for malware. By …