Results 91 to 100 of about 2,945,918 (205)

IRDS4C–CTIB: A Blockchain-Driven Deception Architecture for Ransomware Detection and Intelligence Sharing

Future Internet
This paper introduces a cybersecurity framework that combines a deception-based ransomware detection system, called the Intrusion and Ransomware Detection System for Cloud (IRDS4C), with a blockchain-enabled Cyber Threat Intelligence platform (CTIB). The
Ahmed El-Kosairy, Heba Aslan, Nashwa AbdelBaki   +2 more
doaj   +1 more source

Enhancing ransomware defense: deep learning-based detection and family-wise classification of evolving threats [PDF]

PeerJ Computer Science
Ransomware is a type of malware that locks access to or encrypts its victim’s files for a ransom to be paid to get back locked or encrypted data. With the invention of obfuscation techniques, it became difficult to detect its new variants.
Amjad Hussain, Ayesha Saadia, Musaed Alhussein, Ammara Gul, Khursheed Aurangzeb   +4 more
doaj   +2 more sources

Neutralization Method of Ransomware Detection Technology Using Format Preserving Encryption. [PDF]

Sensors (Basel), 2023
Lee J, Lee SY, Yim K, Lee K.
europepmc   +1 more source

Effective Ransomware Detection Using Entropy Estimation of Files for Cloud Services. [PDF]

Sensors (Basel), 2023
Lee K, Lee J, Lee SY, Yim K.
europepmc   +1 more source

Dynamic Feature Dataset for Ransomware Detection Using Machine Learning Algorithms. [PDF]

Sensors (Basel), 2023
Herrera-Silva JA, Hernández-Álvarez M.
europepmc   +1 more source

Enhancing Ransomware Detection with a Hybrid Deep Learning Approach: Integrating Convolutional Neural Networks and Long Short-Term Memory Networks for a Robust Cybersecurity Solution

Engineered Science
Ransomware attacks continue to be a significant and evolving cybersecurity threat, with traditional detection techniques often unable to identify new and sophisticated variants.
Priynka Sharma, Kaylash Chaudhary
doaj   +1 more source

ProtectNIC - SmartNIC Ransomware Detection [PDF]

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   +1 more source

Detecting Ransomware

, 2018
Ransomware attacks -- in contrast to other cyber attacks -- must not be detected and especially not blocked or recovered on first sight. This relaxation is supported by the rareness of ransomware attacks. Certainly, the uprising of ransomware families, which are able to circumvent the detection mechanism, integrated into the local machine, prevents the
openaire   +1 more source

Ransomware detection using deep learning based unsupervised feature extraction and a cost sensitive Pareto Ensemble classifier. [PDF]

Sci Rep, 2022
Zahoora U, Khan A, Rajarajan M, Khan SH, Asam M, Jamal T.   +5 more
europepmc   +1 more source

An intelligent ransomware based cyberthreat detection model using multi head attention-based recurrent neural networks with optimization algorithm in IoT environment

Scientific Reports
The rapid growth of the Internet of Things (IoT) and its extensive use in many regions, such as smart homes, healthcare, and vehicles, have made IoT security increasingly critical.
Sarah A. Alzakari, Mohammed Aljebreen, Nazir Ahmad, Asma A. Alhashmi, Sultan Alahmari, Othman Alrusaini, Ali M. Al-Sharafi, Wafa Sulaiman Almukadi   +7 more
doaj   +1 more source