A Robust Framework for MADS Based on DL Techniques on the IoT
Day after day, new types of malware are appearing, renewing, and continuously developing, which makes it difficult to identify and stop them. Some attackers exploit artificial intelligence (AI) to create renewable malware with different signatures that are difficult to detect. Therefore, the perform...
Saved in:
Main Authors: | Hussah Talal, Rachid Zagrouba |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/8d91ad0d89bd4fb7b5e751697514d8e4 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
MADS Based on DL Techniques on the Internet of Things (IoT): Survey
by: Hussah Talal, et al.
Published: (2021) -
A survey and taxonomy of program analysis for IoT platforms
by: Alyaa A. Hamza, et al.
Published: (2021) -
IoT Dataset Validation Using Machine Learning Techniques for Traffic Anomaly Detection
by: Laura Vigoya, et al.
Published: (2021) -
Shape adaptive IRS based SAG IoT network
by: Fei Qi, et al.
Published: (2021) -
An Anomaly-Based Intrusion Detection System for Internet of Medical Things Networks
by: Georgios Zachos, et al.
Published: (2021)