Results 51 to 60 of about 9,054 (204)

Comparative Study of Fileless Ransomware

, 2020
A Fileless Ransomware is a new type of ransomware primarily follows the mechanism of both ransomware and fileless malware. Detecting and Defending these kinds of attacks becoming a great obstacle for IT firms.
Krishna B L
core   +1 more source

RanViz: Ransomware Visualization and Classification Based on Time-Series Categorical Representation of API Calls

IEEE Access
Ransomware continues to pose a significant threat to individuals and organizations worldwide, causing disruptions, financial losses, and reputational damage.
Vhuhwavho Mokoma, Avinash Singh
doaj   +1 more source

Ransomware detection based on machine learning models and Event Tracing for Windows

Безопасность информационных технологий, 2022
Nowadays ransomware cyberattacks are alarmingly increasing. Ransomware is a form of malicious software that locks users’ files by modifying it or it’s parts. To get the files back the users are supposed to pay ransom. Ransomware are using different types
Artem O. Kalinkin, Svetlana A. Golub, Igor Y. Korkin, Danil N. Pyatovskiy   +3 more
doaj   +1 more source

RansomFisher: Behavior-based ransomware detection without decoys

ICT Express
Ransomware remains a significant cyber threat for legacy and recent systems. This study revisits behavior-based detection and introduces RansomFisher, a novel decoyless ransomware detection system that monitors file access patterns.
InHoe Ku, Iljun Jeong, Seunghun Han
doaj   +1 more source

A behavioural in‐depth analysis of ransomware infection

IET Information Security, 2021
Ransomware is a type of malware that has spread rapidly over the last 4 years, causing significant damage, especially in Windows environments. It is designed to encrypt or block victim's data, including documents, backups, and databases, unless a ransom ...
Yassine Lemmou, Jean‐Louis Lanet, El Mamoun Souidi   +2 more
doaj   +1 more source

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha, Mohammad Kamrul Hasan, Shayla Islam, Shailesh Khapre, Salwani Abdullah, Taher M. Ghazal, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nguyen Vo, Md Akhtaruzzaman   +9 more
wiley   +1 more source

Unveiling evasive ransomware and breaking through the predicament: a comprehensive review of evasion techniques and defense mechanisms

Cybersecurity
Ransomware has become one of the most destructive cyberattacks worldwide in recent years and has caused billions of dollars. Numerous defense mechanisms have been proposed to mitigate the ransomware threat.
Lingbo Zhao, Shuquan Wang, Yuhui Zhang, Rui Hou   +3 more
doaj   +1 more source

A Survey of Crypto Ransomware Attack Detection Methodologies: An Evolving Outlook

Sensors, 2022
Recently, ransomware attacks have been among the major threats that target a wide range of Internet and mobile users throughout the world, especially critical cyber physical systems.
Abdullah Alqahtani, Frederick T. Sheldon
doaj   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

Android Ransomware Detection From Traffic Analysis Using Metaheuristic Feature Selection

IEEE Access, 2022
Among the prevalent cyberattacks on Android devices, a ransomware attack is the most common and damaging. Although there are many solutions for detecting Android ransomware attacks, existing solutions have limited detection accuracy and high ...
Md. Sakir Hossain, Naim Hasan, Md. Abdus Samad, Hossain Md. Shakhawat, Joydeep Karmoker, Foysol Ahmed, K. F. M. Nafiz Fuad, Kwonhue Choi   +7 more
doaj   +1 more source