FeSAD ransomware detection framework with machine learning using adaption to concept drift

Author:

Fernando Damien WarrenORCID,Komninos NikosORCID

Funder

INTO City University London

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference33 articles.

1. A system call refinement-based enhanced minimum redundancy maximum relevance method for ransomware early detection;Ahmed;J. Netw. Comput. Appl.,2020

2. Multi-classifier network-based crypto ransomware detection system: a case study of locky ransomware;Almashhadani;IEEE Access,2019

3. API-based ransomware detection using machine learning-based threat detection models;Almousa,2021

4. An I/O request packet (IRP) driven effective ransomware detection scheme using artificial neural network;Ayub,2020

5. Transcending transcend: revisiting malware classification in the presence of concept drift;Barbero,2022

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