BiTA: Bidirectional Gated Recurrent Unit-Transformer Aggregator in a Temporal Graph Network Framework for Alert Prediction in Computer Networks

This research introduces BiTA, a novel Bidirectional Gated Recurrent Unit-Transformer Aggregator, designed to enhance proactive alert prediction in computer networks. It redesigns temporal aggregation in Temporal Graph Neural Networks to capture complex, multi-scale temporal patterns by jointly encoding bidirectional sequential dependencies and long-range contextual relations.