A Comprehensive Review of Machine Learning-Based Malware Detection Techniques for Windows Platform

A Wajid, T Ahmed, UB Chaudhry - The Nucleus, 2024 - thenucleuspak.org.pk
The growing threat of windows malware poses an increasing risk to the security of
computers and the sensitive information they hold. The exponential rise in malware threats …

PSAU-Defender: a Device-Agnostic Approach to Defend Against Ransomware Vulnerabilities

U Tariq - Kurdish Studies, 2024 - kurdishstudies.net
This research provides a comprehensive analysis of the lifecycle and characteristics of
ransomware attacks, aiming to establish a robust foundation for future studies in the field …

[PDF][PDF] Ransomware Detection Using Machine Learning: A Review, Research Limitations and Future Directions

MDZ ISLAM - 2024 - researchoutput.csu.edu.au
Ransomware attacks are on the rise in terms of both frequency and impact. The shift to
remote work due to the COVID-19 pandemic has led more people to work online, prompting …

Malware Profiling and Classification using machine learning algorithms

H Rathee - 2024 - esource.dbs.ie
The study done on" Malware Profiling and Classification using Machine Learning
Algorithms" compares multiple machine learning models for malware detection and profiling …

Enhancing Ransomware Detection: A Windows API Min Max Relevance Refinement Approach

Q Kang, Y Gu - 2023 - preprints.org
Ransomware constitutes a distinctive category of pernicious software that sequesters a
user's digital assets by encryption, holding them hostage until a sum is extorted from the …

[图书][B] Ransomware Detection with XGBoost Hardware Acceleration for Data Centers Using High-Level Synthesis

A Gajjar - 2023 - search.proquest.com
Over the last decade, the cybersecurity community observed a surge in cybersecurity
attacks, especially ransomware due to its notoriously costly and turbulent impact on the …

Defeating Evasive Malware with Peekaboo: Extracting Authentic Malware Behavior with Dynamic Binary Instrumentation

M Gaber, M Ahmed, H Janicke - 2024 - researchsquare.com
Abstract The accuracy of Artificial Intelligence (AI) in malware detection is dependent on the
features it is trained with, where the quality and authenticity of these features is dependent …

[PDF][PDF] Ransomware Detection by Cognitive Security (en inglés)

SPS Gordón - 2023 - doctoradoinformatica.epn.edu.ec
Ransomware-related cyber-attacks have been on the rise over the last decade, disturbing
organizations considerably. Developing new and better ways to detect this type of malware …

[HTML][HTML] 1.1 Malware Categorization

SS Hussain, MF Ab Razak, A Firdaus - journals.riverpublishers.com
There are several ways to categories the malware based on its nature of detection, pattern,
and behaviour etc. Behavior-based or signature-based techniques are the two primary types …

Técnicas de machine Learning para la detección de Ransomware: Revisión sistemática de Literatura

OMC Pineda, PVL Preciado… - Journal of Science and …, 2022 - revistas.utb.edu.ec
El ransomware es uno de los problemas de seguridad informática más críticos, es un tipo de
malware que cifra o bloquea la información de la víctima para solicitar el pago de un rescate …