Results 81 to 90 of about 1,242 (180)

Machine learning-based ransomware classification of Bitcoin transactions

Journal of King Saud University: Computer and Information Sciences
Ransomware presents a significant threat to the security and integrity of cryptocurrency transactions. This research paper explores the intricacies of ransomware detection in cryptocurrency transactions using the Bitcoinheist dataset.
Omar Dib, Zhenghan Nan, Jinkua Liu
doaj   +1 more source

Blockchain security for ransomware detection

This manuscript was submitted to the journal TELKOMNIKA (https://www.scopus.com/sourceid/21100256101). Title: "Interpretable machine learning for ransomware detection". Status: Under review. Dataset and code available at Mike Nkongolo Wa Nkongolo (2023). UGRansome dataset. Kaggle. https://www.kaggle.com/dsv/7172543 [Accessed 23 July 2024].
Mutombo, Elodie Ngoie, Nkongolo, Mike Wa
openaire   +2 more sources

Majority Voting Ransomware Detection System

Journal of Information Security, 2023
Simon R. Davies, Richard Macfarlane, William J. Buchanan   +2 more
openaire   +1 more source

XRGuard: A Model-Agnostic Approach to Ransomware Detection Using Dynamic Analysis and Explainable AI

IEEE Access
Ransomware remains a persistent and evolving cybersecurity threat, demanding advanced and adaptable detection strategies. Traditional methods often fall short as signature-based systems are easily circumvented by emerging ransomware variants, while ...
M. Adnan Alvi, Zunera Jalil
doaj   +1 more source

Ransomware Detection by Machine Learning

International Journal for Research in Applied Science and Engineering Technology
Ransomware detection remains a critical component of endpoint security across workstations, servers, cloud environments, and mobile devices. The escalating volume and sophistication of ransomware variants pose significant challenges to traditional signature-based and heuristic detection techniques.
openaire   +1 more source

Novel Ransomware Detection Exploiting Uncertainty and Calibration Quality Measures Using Deep Learning

Information
Ransomware poses a significant threat by encrypting files or systems demanding a ransom be paid. Early detection is essential to mitigate its impact. This paper presents an Uncertainty-Aware Dynamic Early Stopping (UA-DES) technique for optimizing Deep ...
Mazen Gazzan, Frederick T. Sheldon
doaj   +1 more source

Ransomware Detection And Prevention

International Journal of Computer Sciences and Engineering, 2018
Annu ., Monika Poriye, Vinod Kumar
openaire   +1 more source

Analysis and detection of ransomware

, 2019
This phD thesis takes a look atransomware, presents an autonomous malwareanalysis platform and proposes countermeasure against these types of attacks. Our countermeasures are real-time and are deployed on a machine(i.e., end-hosts). In 2013, the ransomware become a hot subject of discussion again, before becomingone of the biggest cyberthreats ...
openaire   +1 more source

Ensemble machine learning for proactive android ransomware detection using network traffic. [PDF]

Sci Rep
Kirubavathi G, Padma Mayuri B, Pranathasree S, Alagappan R, Ajayan A, Ismael WM, Rehman AU.   +6 more
europepmc   +1 more source

An Intelligent Sensing Framework for Early Ransomware Detection Using MHSA-LSTM Machine Learning. [PDF]

Sensors (Basel)
Alqahtani A, Ohemeng MO, Sheldon FT.
europepmc   +1 more source