Optimizing blue team strategies with reinforcement learning for enhanced ransomware defense simulations

S Wang, Y Li, F Chen - Authorea Preprints, 2024 - authorea.com
Ransomware has rapidly evolved into one of the most significant threats to organizational
cybersecurity, with its ability to disrupt operations and cause extensive financial and data …

Forensic analysis of live ransomware attacks on linux-based laptop systems: Techniques and evaluation

W Neweva, O Fitzwilliam, J Waterbridge - 2024 - researchsquare.com
The increasing prevalence of ransomware attacks targeting Linux-based systems has
highlighted the critical need for effective detection and mitigation strategies that can operate …

[PDF][PDF] Advanced ransomware detection and classification via semantic analysis of memory opcode patterns

T Lowev, C Fisher, J Collins - 2024 - files.osf.io
Ransomware attacks have become one of the most prevalent and damaging forms of cyber
threats, with their increasing sophistication posing significant challenges to traditional …

Prediction of android ransomware with deep learning model using hybrid cryptography

KR Kalphana, S Aanjankumar, M Surya… - Scientific Reports, 2024 - nature.com
In recent times, the number of malware on Android mobile phones has been growing, and a
new kind of malware is Android ransomware. This research aims to address the emerging …

Enhancing network intrusion detection using effective stacking of ensemble classifiers with multi-pronged feature selection technique

S Rahman, SNF Mursal, MA Latif… - … on Emerging Trends …, 2023 - ieeexplore.ieee.org
Information security depends on Network Intrusion Detection (NID), which properly identifies
network threats. This work explores simulating a NID system by stacking ensemble …

An intelligent ransomware attack detection and classification using dual vision transformer with Mantis Search Split Attention Network

K Ashwini, KB Nagasundara - Computers and Electrical Engineering, 2024 - Elsevier
Ransomware attacks pose significant cybersecurity threats, compromising computer
systems, data centers and various applications across sectors. Their sophistication …

Ransomware detection using machine learning: A review, research limitations and future directions

J Ispahany, MDR Islam, MZ Islam, MA Khan - IEEE Access, 2024 - ieeexplore.ieee.org
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 …

A Deep Transfer Learning Framework for Robust IoT Attack Detection

HA Mohammed, IM Husien - Informatica, 2024 - informatica.si
Our lives have been significantly altered due to the digital revolution, and the Internet of
Things (IoT) has played a significant part in this transformation. However, the fast expansion …

Ransomware detection dynamics: Insights and implications

M Nkongolo - arXiv preprint arXiv:2402.04594, 2024 - arxiv.org
The rise of ransomware attacks has necessitated the development of effective strategies for
identifying and mitigating these threats. This research investigates the utilization of a feature …

Augmenting Aquaculture Efficiency through Involutional Neural Networks and Self-Attention for Oplegnathus Punctatus Feeding Intensity Classification from Log Mel …

U Iqbal, D Li, Z Du, M Akhter, Z Mushtaq, MF Qureshi… - Animals, 2024 - mdpi.com
Simple Summary Managing fish feeding well is important for both making fish farming better
and keeping aquatic environments healthy. By looking at the sounds fish make, this study …