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 …
[HTML][HTML] A systematic literature review on windows malware detection: Techniques, research issues, and future directions
The aim of this systematic literature review (SLR) is to provide a comprehensive overview of
the current state of Windows malware detection techniques, research issues, and future …
the current state of Windows malware detection techniques, research issues, and future …
IGRF-RFE: a hybrid feature selection method for MLP-based network intrusion detection on UNSW-NB15 dataset
The effectiveness of machine learning models can be significantly averse to redundant and
irrelevant features present in the large dataset which can cause drastic performance …
irrelevant features present in the large dataset which can cause drastic performance …
Ransomware detection using deep learning based unsupervised feature extraction and a cost sensitive Pareto Ensemble classifier
Ransomware attacks pose a serious threat to Internet resources due to their far-reaching
effects. It's Zero-day variants are even more hazardous, as less is known about them. In this …
effects. It's Zero-day variants are even more hazardous, as less is known about them. In this …
Crypto-ransomware: A revision of the state of the art, advances and challenges
According to the premise that the first step to try to solve a problem is to deepen our
knowledge of it as much as possible, this work is mainly aimed at diving into and …
knowledge of it as much as possible, this work is mainly aimed at diving into and …
Artificial intelligence-enabled DDoS detection for blockchain-based smart transport systems
A smart public transport system is expected to be an integral part of our human lives to
improve our mobility and reduce the effect of our carbon footprint. The safety and ongoing …
improve our mobility and reduce the effect of our carbon footprint. The safety and ongoing …
FAMCF: A few-shot Android malware family classification framework
Android malware is a major cyber threat to the popular Android platform which may
influence millions of end users. To battle against Android malware, a large number of …
influence millions of end users. To battle against Android malware, a large number of …
From data and model levels: Improve the performance of few-shot malware classification
Y Chai, J Qiu, L Yin, L Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Existing malware classification methods cannot handle the open-ended growth of new or
unknown malware well because it only focuses on pre-defined malware classes with …
unknown malware well because it only focuses on pre-defined malware classes with …
Self-supervised metalearning generative adversarial network for few-shot fault diagnosis of hoisting system with limited data
Y Li, F Xu, CG Lee - IEEE Transactions on Industrial Informatics, 2022 - ieeexplore.ieee.org
Few-shot data collected from hoisting system suffer from inadequate information in the
practical industries, which reduces the diagnostic accuracy of the data-driven-based fault …
practical industries, which reduces the diagnostic accuracy of the data-driven-based fault …
[HTML][HTML] Ransomware early detection: A survey
In recent years, ransomware attacks have exploded globally, and it has become one of the
most significant cyber threats to digital infrastructure. Such attacks have been targeting …
most significant cyber threats to digital infrastructure. Such attacks have been targeting …