This paper introduces a novel approach to detecting distributed denial of service (DDoS) attacks in internet service provider (ISP) core networks. The solution uses a digital twin-enabled intelligent DDoS detection mechanism and an online learning method for autonomous systems. The authors argue that existing DDoS solutions are inadequate for ISP core networks due to the high volume of data. Their proposed solution, which includes a DDoS detection architecture based on digital twin technology, a Yet Another Next Generation (YANG) model, and an automated feature selection (AutoFS) module, reportedly detects DDoS attacks with a 97% true classification rate and can estimate an attack within approximately fifteen minutes of its start.
Publication date: 20 Oct 2023
Project Page: Not provided
Paper: https://arxiv.org/pdf/2310.12924
