计算机科学 ›› 2012, Vol. 39 ›› Issue (8): 62-66.

• 计算机网络与信息安全 • 上一篇    下一篇

无线Mesh网络基于隐半马尔可夫模型的跨层结合异常检测方法

王涛,吴晓燕,程良伦   

  1. (广东工业大学自动化学院 广州 510006) (四川文理学院计算机科学系 达州 635000)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Cross-layer Based Anomaly Detection Mechanism with Hidden Semi-Markov

  • Online:2018-11-16 Published:2018-11-16

摘要: 目前无线Mesh网络异常检测的方法大多针对单一恶意攻击,还不具备检测来自不同协议层的恶意攻击的 综合能力。提出一种基于多协议层跨层结合的异常检测方法,即采集多协议层结合的特征对网络运行状态进行全方 位监测,并训练隐半马尔可夫模型对网络正常运行状态进行描述,通过计算多维观测序列相对于隐半马尔可夫模型的 嫡来评价其“正常性”,从而发现源自不同协议层的恶意攻击行为。实验仿真证明,该方法能有效检测源自各协议层的 多种恶意攻击,具有一定的通用性。

关键词: 无线Mesh网络,跨层结合,观测序列,隐半马尔可夫模型,异常检测

Abstract: The existing methods on anomaly detection in wireless Mesh network mostly focus on single malicious at- tack, which can not detect various malicious attacks originated form different protocol layers. We presented a cross-layer based anomaly detection mechanism. Firstly a distributed )DS structure for Mesh backbone network topology was pro- posed, secondly cross-layer based features were collected for comprehensively monitoring network activities. Further- more,with the multidimensional observation sequences, the hidden semi-Markov model(HsMM) was trained and ex- ploited to characterize and model the normal states of network activities. The entropies of observation secfuences against the HsMM were calculated to evaluate their abnormality. An anomaly alert will be reported if the entropy is lower than a threshold. Experiment results show that the proposed detection mechanism is able to detect various malicious attacks from different protocol layers.

Key words: Wireless Mesh network, Cross-layer based, Observation sequences, Hidden semi-Markov model, Anomalydctc(tion

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