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

BiTA模型增强了用于网络警报预测的时间图网络

研究人员开发了BiTA,一种新颖的双向门控循环单元-Transformer聚合器,专为时间图网络设计。该框架通过更好地捕捉攻击行为中复杂的时间模式,增强了计算机网络中的警报预测能力。BiTA通过联合编码节点时间邻域内的双向序列依赖性和长程上下文关系来实现这一点,在归纳和推导设置中均优于现有模型。 AI

影响 引入了一个用于改进网络威胁预测和入侵检测系统的新框架。

排序理由 这是一篇介绍用于计算机网络警报预测新框架的研究论文。

在 arXiv cs.LG 阅读 →

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BiTA模型增强了用于网络警报预测的时间图网络

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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Zahra Makki Nayeri, Mohsen Rezvani ·

    BiTA:计算机网络中用于警报预测的双向门控循环单元-Transformer聚合器在时间图网络框架中的应用

    arXiv:2604.22781v1 Announce Type: new Abstract: Proactive alert prediction in computer networks is critical for mitigating evolving cyber threats and enabling timely defensive actions. Temporal Graph Neural Networks (TGNs) provide a principled framework for modeling time-evolving…