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1. 浙江大学城市学院计算机与计算科学学院 杭州310015
2. 浙江大学计算机学院 杭州310027
[ "陈观林,男,博士,浙江大学城市学院副教授、硕士生导师,主要研究方向为网络安全。" ]
[ "王泽兵,男,浙江大学城市学院教授、硕士生导师,主要研究方向为网络与数据库技术。" ]
[ "张泳,男,浙江大学城市学院副教授,主要研究方向为计算机应用。" ]
网络出版日期:2013-11,
纸质出版日期:2013-11-20
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陈观林, 王泽兵, 张泳. 面向WLAN的分布式无线多步攻击模式挖掘方法研究[J]. 电信科学, 2013,29(11):38-44.
Guanlin Chen, Zebing Wang, Yong Zhang. Research on Distributed Wireless Multi-Step Attack Pattern Mining Method for WLAN[J]. Telecommunications science, 2013, 29(11): 38-44.
陈观林, 王泽兵, 张泳. 面向WLAN的分布式无线多步攻击模式挖掘方法研究[J]. 电信科学, 2013,29(11):38-44. DOI: 10.3969/j.issn.1000-0801.2013.11.007.
Guanlin Chen, Zebing Wang, Yong Zhang. Research on Distributed Wireless Multi-Step Attack Pattern Mining Method for WLAN[J]. Telecommunications science, 2013, 29(11): 38-44. DOI: 10.3969/j.issn.1000-0801.2013.11.007.
入侵检测和防御技术作为网络安全防护的重要手段,在传统有线网络环境中已有较为成熟的应用。但由于无线网络的特殊性,仍很少看到WLAN领域无线多步攻击规划识别的研究。提出了一种融合IEEE 802.11协议帧主要属性进行关联分析的分布式无线多步攻击模式挖掘(DWMAPM)方法。该方法包括构造全局攻击库、建立候选攻击链、筛选候选攻击链、关联多步攻击行为和识别多步攻击模式5个步骤。实验结果表明,DWMAPM方法能够适用于WLAN的真实攻击场景,有效挖掘出多种常见的无线多步攻击模式,可以为多步攻击意图预先识别提供基础。
As the important means of network security
intrusion detection and prevention technology have seen some preliminary applications in the traditional wired network environment. Due to the distinctive characteristics of wireless network
the applications of multi-stage attack plan recognition for WLAN are rarely seen in spite of the promising potential. A distributed wireless multi-step attack pattern mining(DWMAPM)method based on correlation analysis with the IEEE 802.11 protocol frame attributes was proposed. The method consists of five steps:constructing a global attack database
building candidate attack chains
filtering candidate attack chains
correlating multi-step attack behaviors and recognizing multi-step attack patterns. Experimental results show that DWMAPM is effective for recognizing a variety of typical attack patterns in real WLAN attack scenarios
and can provide a basis for forecasting the final attack plans.
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陈观林 , 冯雁 , 王泽兵 . 分布式无线入侵防御系统预先决策引擎研究 . 电信科学 , 2010 , 26 ( 10 ): 80 ~ 86
Geib C W , Goldman R P . Plan recognition in intrusion detection systems . Proceedings of DARPA Information Survivability Conference and Exposition(DISCEX IIˊ01) , Anaheim,USA , 2001
Geib C W , Goldman R P . Probabilistic plan recognition for hostile agents . Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2001) , Key West, USA , 2001
Sheyner O , Haines J , Jha S , et al . Automated generation and analysis of attack graphs . Proceedings of the 2002 IEEE Symposium on Security and Privacy(SP'02) , Oakland, USA , 2002
Ning P , Cui Y , Reeves D S . Constructing attack scenarios through correlation of intrusion alerts . Proceedings of the 9th ACM Conference on Computer and Communications Security (CCS'02) , Washington, DC, USA , 2002
Ning P , Cui Y , Reeves D S , et al . Techniques and tools for analyzing intrusion alerts . ACM Transactions on Information and System Security , 2004 , 7 ( 2 ): 274 ~ 318
Cuppens F , Miège A . Alert correlation in a cooperative intrusion detection framework . Proceedings of the IEEE Symposium on Security and Privacy , Oakland, California, USA , 2002
Hellerstein J L , Ma S , Perng C S . Discovering actionable patterns in event data . IBM Systems Journal , 2002 , 41 ( 3 ): 475 ~ 493
Qin X Z , Lee W K . Attack plan recognition and prediction using causal networks . Proceedings of the 20th Annual Computer Security Applications Conference(ACSAC 2004) , Tucson, USA , 2004
Wang L , Ghorbani A , Li Y . Automatic multi-step attack pattern discovering . International Journal of Network Security , 2010 , 10 ( 2 ): 142 ~ 152
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