[HTML][HTML] Intelligent and dynamic ransomware spread detection and mitigation in integrated clinical environments

L Fernandez Maimo, A Huertas Celdran… - Sensors, 2019 - mdpi.com
Medical Cyber-Physical Systems (MCPS) hold the promise of reducing human errors and
optimizing healthcare by delivering new ways to monitor, diagnose and treat patients …

Leveraging deep learning models for ransomware detection in the industrial internet of things environment

M Al-Hawawreh, E Sitnikova - 2019 military communications …, 2019 - ieeexplore.ieee.org
Local Area Network (LAN) workstations that operate at the edge tier of Industrial Internet of
Things systems (IIoT) and have direct or indirect interaction with critical control devices could …

[HTML][HTML] A survey of crypto ransomware attack detection methodologies: an evolving outlook

A Alqahtani, FT Sheldon - Sensors, 2022 - mdpi.com
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 …

[HTML][HTML] E2E-RDS: Efficient End-to-End ransomware detection system based on Static-Based ML and Vision-Based DL approaches

I Almomani, A Alkhayer, W El-Shafai - Sensors, 2023 - mdpi.com
Nowadays, ransomware is considered one of the most critical cyber-malware categories. In
recent years various malware detection and classification approaches have been proposed …

Systematic literature review and metadata analysis of ransomware attacks and detection mechanisms

AM Maigida, SM Abdulhamid, M Olalere… - Journal of Reliable …, 2019 - Springer
Ransomware is advanced and upgraded malicious software which comes in the forms of
Crypto or Locker, with the intention to attack and take control of basic infrastructures and …

[HTML][HTML] Dynamic feature dataset for ransomware detection using machine learning algorithms

JA Herrera-Silva, M Hernández-Álvarez - Sensors, 2023 - mdpi.com
Ransomware-related cyber-attacks have been on the rise over the last decade, disturbing
organizations considerably. Developing new and better ways to detect this type of malware …

[HTML][HTML] 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 …

A multi-classifier network-based crypto ransomware detection system: A case study of locky ransomware

AO Almashhadani, M Kaiiali, S Sezer, P O'Kane - IEEE access, 2019 - ieeexplore.ieee.org
Ransomware is a type of advanced malware that has spread rapidly in recent years, causing
significant financial losses for a wide range of victims, including organizations, healthcare …

A survey on machine learning-based ransomware detection

N Rani, SV Dhavale, A Singh, A Mehra - Proceedings of the Seventh …, 2022 - Springer
Ransomware is a program used by an attacker or hacker, that locks or encrypts target files or
data. The user or the owner of data cannot access these without the explicit assistance of the …

Improving ransomware detection based on portable executable header using xception convolutional neural network

CC Moreira, DC Moreira, CS de Sales Jr - Computers & Security, 2023 - Elsevier
All malware are harmful to computer systems; however, crypto-ransomware specifically
leads to irreparable data loss and causes substantial economic prejudice. Ransomware …