Visualized Malware Multi-Classification Framework Using Fine-Tuned CNN-Based Transfer Learning Models
There is a massive growth in malicious software (Malware) development, which causes substantial security threats to individuals and organizations. Cybersecurity researchers makes continuous efforts to defend against these malware risks. This research aims to exploit the significant advantages of Tra...
Main Authors: | Walid El-Shafai, Iman Almomani, Aala AlKhayer |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/14/6446 |
Similar Items
-
MSIC: Malware Spectrogram Image Classification
by: Ahmad Azab, et al.
Published: (2020-01-01) -
An Efficient DenseNet-Based Deep Learning Model for Malware Detection
by: Jeyaprakash Hemalatha, et al.
Published: (2021-03-01) -
MVFCC: A Multi-View Fuzzy Consensus Clustering Model for Malware Threat Attribution
by: Hamed Haddadpajouh, et al.
Published: (2020-01-01) -
A New Malware Classification Framework Based on Deep Learning Algorithms
by: Omer Aslan, et al.
Published: (2021-01-01) -
A New Proposal on the Advanced Persistent Threat: A Survey
by: Santiago Quintero-Bonilla, et al.
Published: (2020-06-01)