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 …
Ransomware detection using machine learning: A survey
A Alraizza, A Algarni - Big Data and Cognitive Computing, 2023 - mdpi.com
Ransomware attacks pose significant security threats to personal and corporate data and
information. The owners of computer-based resources suffer from verification and privacy …
information. The owners of computer-based resources suffer from verification and privacy …
An investigation into the performances of the state-of-the-art machine learning approaches for various cyber-attack detection: A survey
In this research, we analyzed the suitability of each of the current state-of-the-art machine
learning models for various cyberattack detection from the past 5 years with a major …
learning models for various cyberattack detection from the past 5 years with a major …
SINN-RD: Spline interpolation-envisioned neural network-based ransomware detection scheme
Multiple kinds of ransomware are currently posing a growing threat to the Internet users.
Important user data is encrypted by the trendy ransomware, and its recovery requires …
Important user data is encrypted by the trendy ransomware, and its recovery requires …
Crypto-ransomware: A revision of the state of the art, advances and challenges
JA Gómez Hernández, P García Teodoro… - Electronics, 2023 - mdpi.com
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 …
Machine Learning in Metaverse Security: Current Solutions and Future Challenges
The Metaverse, positioned as the next frontier of the Internet, has the ambition to forge a
virtual shared realm characterized by immersion, hyper-spatiotemporal dynamics, and self …
virtual shared realm characterized by immersion, hyper-spatiotemporal dynamics, and self …
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 …
devices and objects of all types on the internet. IoT cybersecurity is the task of protecting …
Threat analysis model to control IoT network routing attacks through deep learning approach
K Janani, S Ramamoorthy - Connection Science, 2022 - Taylor & Francis
Most of the recent research has focused on the Internet of Things (IoT) and its applications.
The open interface and network connectivity of the interconnected systems under the IoT …
The open interface and network connectivity of the interconnected systems under the IoT …
Offensive security: Cyber threat intelligence enrichment with counterintelligence and counterattack
Cyber-attacks on financial institutions and corporations are on the rise, particularly during
pandemics. These attacks are becoming more sophisticated. Reports of hacking activities …
pandemics. These attacks are becoming more sophisticated. Reports of hacking activities …
Api2vec++: Boosting api sequence representation for malware detection and classification
Analyzing malware based on API call sequences is an effective approach, as these
sequences reflect the dynamic execution behavior of malware. Recent advancements in …
sequences reflect the dynamic execution behavior of malware. Recent advancements in …