A Scalable Framework for Real-Time Network Security Traffic Analysis and Attack Detection Using Machine and Deep Learning
This paper presents an advanced framework for real-time monitoring and analysis of network traffic and endpoint security in large-scale enterprises by addressing the increasing complexity and frequency of cyber-attacks. Our Network Security Traffic Analysis Platform employs a comprehensive technolog...
Saved in:
Main Authors: | Zineb Maasaoui, Mheni Merzouki, Abdella Battou, Ahmed Lbath |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-04-01
|
Series: | Platforms |
Subjects: | |
Online Access: | https://www.mdpi.com/2813-4176/3/2/7 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Big Data Framework for Scalable and Cross-Dataset Capable Machine Learning in Network Intrusion Detection Systems
by: Vinicius M. de Oliveira, et al.
Published: (2025-01-01) -
SecFedDNN: A Secure Federated Deep Learning Framework for Edge–Cloud Environments
by: Roba H. Alamir, et al.
Published: (2025-06-01) -
Explainable AI Meets Synthetic Data: A Deep Learning Framework for Detecting Network Intrusion in NextG Network Infrastructure
by: Md Junayed Hossain, et al.
Published: (2025-01-01) -
Adaptive Defense: Zero-Day Attack Detection in NIDS With Deep Reinforcement Learning
by: Khorshed Alam, et al.
Published: (2025-01-01) -
Detecting Unbalanced Network Traffic Intrusions With Deep Learning
by: S. Pavithra, et al.
Published: (2024-01-01)