Protocol-Agnostic and Packet-Based Intrusion Detection Using a Multi-Layer Deep-Learning Architecture at the Network Edge
Intrusion Detection (ID) faces multiple challenges, including the diversity of intrusion types and the risk of false positives and negatives. In an edge computing context, resource constraints further complicate the process, particularly during the training phase, which is computationally intensive....
Saved in:
| Main Authors: | Rodolphe Picot, Felipe Gohring de Magalhaes, Ahmad Shahnejat Bushehri, Maroua Ben Atti, Gabriela Nicolescu, Alejandro Quintero |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10942348/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Leveraging edge learning and game theory for intrusion detection in Internet of things
by: Haoran LIANG, et al.
Published: (2021-06-01) -
Data-driven network intrusion detection using optimized machine learning algorithms
by: Dauda Adeite Adenusi, et al.
Published: (2025-09-01) -
Adversarial Hierarchical-Aware Edge Attention Learning Method for Network Intrusion Detection
by: Hao Yan, et al.
Published: (2025-07-01) -
Research on lightweight non-intrusive load disaggregation model for edge computing
by: YE Canshen, et al.
Published: (2025-05-01) -
Fuzzy intrusion detection system for MANET packet dropping attack
by: Tingting LU, et al.
Published: (2016-10-01)