微型电脑应用

面对分布式网络复杂多变的入侵行为，为了在兼顾防御效率的同时高质量地保证网络安全，提出基于时态知识模型的分布式网络入侵混合防御方法。利用时态知识模型捕捉分布式网络的时态流量特征，根据这些特征区分正常流量和异常流量；根据区分结果，检测网络入侵行为，生成流量黑名单，并通过实时匹配流量特征，设计混合防御架构。该架构一旦检测到异常情况，将立即触发防御机制。实验结果表明，所提出的方法能够准确识别网络攻击，并且降低了网络安全威胁值。

Facing complex and ever-changing intrusion behaviors in distributed network,in order to ensure network security with high quality while balancing defense efficiency,a hybrid defense method of distributed network intrusion based on temporal knowledge model is proposed.A temporal knowledge model is used to capture the temporal traffic characteristics of the distributed network,distinguish normal traffic and abnormal traffic based on these characteristics.Based on the distinction results,network intrusion behavior is detected and a traffic blacklist is generated.A hybrid defense architecture is designed by real-time matching of traffic characteristics.Once the structure detects abnormal situation,the defense mechanism is immediately triggered.The experimental results show that the proposed method can accurately identify network attacks and reduce network security threat value.