Name
Title | ||
|---|---|---|
Towards Fast Network Intrusion Detection based on Efficiency-preserving Federated Learning |
Abstract | ||
|---|---|---|
Network Intrusion Detection Systems (NIDSs) are extremely important in defending against emergent cyberattacks. However, current NIDSs for Internet-of-Things (IoT) devices have not taken actual device computation limitation into account, and are still based on resource-consuming neural networks. In this paper, we propose a simple but effective FL-based NIDS. Specifically, we leverage the character... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00071 | 2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) |
Keywords | DocType | ISSN |
Intrusion Detection,Communication-efficient,Privacy-preserving,Federated Learning,Internet-of-Things | Conference | 2158-9178 |
ISBN | Citations | PageRank |
978-1-6654-3574-1 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tian Dong | 1 | 24 | 1.43 |
| Han Qiu | 2 | 1 | 2.38 |
| Jialiang Lu | 3 | 33 | 3.33 |
| Meikang Qiu | 4 | 3722 | 246.98 |
| Chun Fan | 5 | 0 | 0.34 |