Ransomware reloaded: Re-examining its trend, research and mitigation in the era of data exfiltration
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 …
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
With the rise in popularity and usage of Android operating systems, malicious applications
are targeted by applying innovative ways and techniques. Today, malware becomes …
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
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 …
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
The struggle between security researchers and malware perpetuates an endless arms race.
Recent studies indicate that converting malware into grayscale images and using …
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
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 …
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 …
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 …
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
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 …
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 …
cyber threats, with ransomware being a primary area of concern. In response to this …
Obfuscated malware detection using dilated convolutional network
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 …
develop rapidly. Consequently, the possible attacks are also evolving. One of the problems …