Ransomware reloaded: Re-examining its trend, research and mitigation in the era of data exfiltration

T McIntosh, T Susnjak, T Liu, D Xu, P Watters… - ACM Computing …, 2024 - dl.acm.org
Ransomware has grown to be a dominant cybersecurity threat by exfiltrating, encrypting, or
destroying valuable user data and causing numerous disruptions to victims. The severity of …

Evaluation and classification of obfuscated Android malware through deep learning using ensemble voting mechanism

S Aurangzeb, M Aleem - Scientific Reports, 2023 - nature.com
With the rise in popularity and usage of Android operating systems, malicious applications
are targeted by applying innovative ways and techniques. Today, malware becomes …

Determination of Gas–Oil minimum miscibility pressure for impure CO2 through optimized machine learning models

C Wu, L **, J Zhao, X Wan, T Jiang, K Ling - Geoenergy Science and …, 2024 - Elsevier
Minimum miscibility pressure (MMP) is one of the most important parameters for designing
CO 2 enhanced oil recovery (EOR) and associated storage in depleted oil reservoirs. The …

FACILE: A capsule network with fewer capsules and richer hierarchical information for malware image classification

B Zou, C Cao, L Wang, S Fu, T Qiao, J Sun - Computers & Security, 2024 - Elsevier
The struggle between security researchers and malware perpetuates an endless arms race.
Recent studies indicate that converting malware into grayscale images and using …

Dwarf mongoose optimization with machine-learning-driven ransomware detection in internet of things environment

K A. Alissa, D H. Elkamchouchi, K Tarmissi, A Yafoz… - Applied Sciences, 2022 - mdpi.com
The internet of things (ransomware refers to a type of malware) is the concept of connecting
devices and objects of all types on the internet. IoT cybersecurity is the task of protecting …

[HTML][HTML] An empirical study of problems and evaluation of IoT malware classification label sources

T Lei, J Xue, Y Wang, T Baker, Z Niu - Journal of King Saud University …, 2024 - Elsevier
With the proliferation of malware on IoT devices, research on IoT malicious code has also
become more mature. Most studies use learning models to detect or classify malware …

Bhmdc: A byte and hex n-gram based malware detection and classification method

Y Tang, X Qi, J **g, C Liu, W Dong - Computers & Security, 2023 - Elsevier
In recent years, malware and their variants have proliferated, which poses a grave threat to
the systems and networks' security, so it is urgent to detect and classify malware in time to …

RThreatDroid: A ransomware detection approach to secure IoT based healthcare systems

MJ Iqbal, S Aurangzeb, M Aleem… - … on Network Science …, 2022 - ieeexplore.ieee.org
The use of smartphone devices in healthcare has increased manifold due to their
widespread use and ease of integration with Internet of Things (IoT) based medical devices …

Combatting ransomware in ZephyrOS-activated industrial IoT environments

U Tariq - Heliyon, 2024 - cell.com
The rapid growth of the Industrial Internet of Things (IIoT) has opened up new avenues for
cyber threats, with ransomware being a primary area of concern. In response to this …

Obfuscated malware detection using dilated convolutional network

A Mezina, R Burget - 2022 14th international congress on ultra …, 2022 - ieeexplore.ieee.org
Nowadays, information security is a critical field of research since information technologies
develop rapidly. Consequently, the possible attacks are also evolving. One of the problems …