Federated Route Leak Detection in Inter-domain Routing with Privacy Guarantee

【Author】 Zeng, Man; Li, Dandan; Zhang, Pei; Xie, Kun; Huang, Xiaohong

【Source】ACM TRANSACTIONS ON INTERNET TECHNOLOGY

【影响因子】3.989

【Abstract】In the inter-domain network, route leaks can disrupt the Internet traffic and cause large outages. The accurate detection of route leaks requires the sharing of AS business relationship information. However, the business relationship information between ASes is confidential. ASes are usually unwilling to reveal this information to the other ASes, especially their competitors. In this paper, we propose a method named FL-RLD to detect route leaks while maintaining the privacy of business relationships between ASes by using a blockchainbased federated learning framework, where ASes can collaboratively train a global detection model without directly disclosing their specific business relationships. To mitigate the lack of ground-truth validation data in route leaks, FL-RLD provides a self-validation scheme by labeling AS triples with local routing policies. We evaluate FL-RLD under a variety of datasets including imbalanced and balanced datasets, and examine different deployment strategies of FL-RLD under different topologies. According to the results, FL-RLD performs better in detecting route leaks than the single AS detection, whether the datasets are balanced or imbalanced. Additionally, the results indicate that selecting ASes with the most peers to first deploy FL-RLD brings more significant benefits in detecting route leaks than selecting ASes with the most providers and customers.

【Keywords】BGP security; route leak detection; federated learning

【发表时间】2023 FEB

【收录时间】2023-05-30

【文献类型】实验仿真

【主题类别】

区块链技术-协同技术-联邦学习