Results 131 to 140 of about 5,693 (213)

Systematic Evaluation of Machine Learning and Deep Learning Models for IoT Malware Detection Across Ransomware, Rootkit, Spyware, Trojan, Botnet, Worm, Virus, and Keylogger. [PDF]

Sensors (Basel)
Maghanaki M, Keramati S, Chen FF, Shahin M.   +3 more
europepmc   +1 more source

Cybersecurity in connected medical devices: a policy agenda for the NHS. [PDF]

NPJ Digit Med
Toparti O, Rajput K, Darzi A, Ghafur S.
europepmc   +1 more source

ProtectNIC - SmartNIC Ransomware Detection

Ransomware, a form of malware that restricts access to data until a ransom is paid, accounts for 20% of all cyber crimes. Although companies and organizations often require their personnel to take training for awareness of such bad actors, social ...
Xu, Anson, Choudhury, Arnav, Liu, Eason
core  

Cyberattacks in supply chains: A multi-case study. [PDF]

PLoS One
Zhang X, Ba X, Li B.
europepmc   +1 more source

A generative AI-driven cybersecurity framework for small and medium enterprises software development: an ANN-ISM approach. [PDF]

Sci Rep
Awan M, Alam A, Khan RA, Alwageed HS, Ayouni S, Almagrabi AO.   +5 more
europepmc   +1 more source

TCCACS and MDR 2026 introduction. [PDF]

Trauma Surg Acute Care Open
Allen M, Patel PP, Mattox KL.
europepmc   +1 more source

Digital Disasters: The Growing Threat of Healthcare Ransomware. [PDF]

Anesthesiology
Tully JL, Gabriel RA, Waterman RS, Dameff CJ.   +3 more
europepmc   +1 more source

A Study of Ransomware Countermeasures

With the significant rise in ransomware attacks in the last decade, the amount of research on mitigating these attacks has also increased. This thesis presents a comprehensive analysis of recent studies on ransomware mitigation, shedding light on the ...
Bhusal, Bipin
core  

Ransomware Attacks and Data Breaches in US Health Care Systems. [PDF]

JAMA Netw Open
Jiang JX, Ross JS, Bai G.
europepmc   +1 more source

Machine learning for Ransomware detection

Este trabalho apresenta o desenvolvimento de um protótipo de ransomware, seguido pela criação e aplicação de um modelo de aprendizado de máquina baseado em floresta aleatória para a detecção de ransomwares.
Breda, Ian Marques [UNESP]
core