Research on Operator Routing Security Technology Based on Transformer

This paper delves into the research and development of a Transformer-based routing security technology framework for network operators, addressing the escalating challenges of routing security amidst the burgeoning scale and intricacy of the internet. Traditional methods of routing security, which are predicated on static rules and manual configurations, are ill-equipped to cope with the dynamic and evolving landscape of cyber threats. The proposed framework harnesses the self-attention mechanisms of the Transformer model to monitor routing updates and traffic data in real-time within operator networks, swiftly identifying and responding to potential security threats. The framework encompasses four principal components: data collection and preprocessing, Transformer-based model design, real-time detection and response, and model updating and optimization. The findings of this paper not only augment the theoretical research within the domain of network security but also provide robust technical support for addressing routing security issues in practical operator network scenarios.