Trusted Multi-Domain DDoS Detection Based on Federated Learning

Aiming at the problems of single detection target of existing distributed denial of service (DDoS) attacks, incomplete detection datasets and privacy caused by shared datasets, we propose a trusted multi-domain DDoS detection method based on federated learning. Firstly, we divide the types of DDoS a...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-10, Vol.22 (20), p.7753
Main Authors: Yin, Ziwei, Li, Kun, Bi, Hongjun
Format: Article
Language:English
Subjects:
Blockchain
Data security
Datasets
DDoS
Denial of service attacks
Domains
federated learning
knowledge base
Knowledge bases (artificial intelligence)
Methods
Network security
Poisoning
Privacy
reputation evaluation
Reputation management
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Summary:Aiming at the problems of single detection target of existing distributed denial of service (DDoS) attacks, incomplete detection datasets and privacy caused by shared datasets, we propose a trusted multi-domain DDoS detection method based on federated learning. Firstly, we divide the types of DDoS attacks into different sub-attacks, design the federated learning dataset for DDoS detection in each domain, and use them to realize a more comprehensive detection method of DDoS attacks on the premise of protecting the data privacy of each domain. Secondly, in order to improve the robustness of federated learning and alleviate poisoning attack, we propose a reputation evaluation method based on blockchain, which estimates interaction reputation, data reputation and resource reputation of each participant comprehensively, so as to obtain the trusted federated learning participants and identify the malicious participants. In addition, we also propose a combination scheme of multi-domain detection and distributed knowledge base and design a feature graph of malicious behavior based on a knowledge graph to realize the memory of multi-domain feature knowledge. The experimental results show that the accuracy of most categories of the multi-domain DDoS detection method can reach more than 95% with the protection of datasets, and the reputation evaluation method proposed in this paper has a higher ability to identify malicious participants against the data poisoning attack when the threshold is set to 0.6.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22207753