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一种低功耗蓝牙DoS攻击检测方案

Scheme for Detecting DoS Attack in Bluetooth Low Energy
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摘要 针对低功耗蓝牙面临Do S攻击威胁的问题,结合熵理论,建立了活跃度模型,依据此模型设计了低功耗蓝牙Do S攻击检测方案,该方案选取多因素构造活跃量,活跃量在正常通信中会呈现稳定的分布规律,当受到Do S攻击时,这种分布规律遭到破坏。用活跃度反映活跃量的分布规律,并通过分析活跃度的变化实现对Do S攻击行为的检测。理论分析与实验结果表明,该方案能有效检测通信中的Do S攻击,同时具有较小的存储和计算开销,适合应用于低功耗蓝牙中。 Aiming at the problem that Bluetooth Low Energy is vulnerable to Do S Attack, an alive degree model combining entropy theory was established. Bluetooth Low Energy Do S Attack detecting scheme based on this model was designed. The scheme chose some elements to construct alive volume, which showed the stable distribution in normal communications, and the distribution was destroyed when subjected to Do S attacks. Using alive degree to reflect the distribution of alive volume, the Do S Attack was detected via the variation of alive degree. The theory analysis and experiment results show that, the scheme can effectively detect the Do S Attack in the communication with low storage and calculation overhead, which is suited for Bluetooth Low Energy.
出处 《系统仿真学报》 CAS CSCD 北大核心 2016年第6期1365-1371,共7页 Journal of System Simulation
关键词 低功耗蓝牙 DOS攻击检测 活跃量 活跃度 Bluetooth Low Energy DoS Attack detecting alive volume alive degree
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  • 1诸葛建伟,王大为,陈昱,叶志远,邹维.基于D-S证据理论的网络异常检测方法[J].软件学报,2006,17(3):463-471. 被引量:56
  • 2曾嘉,金跃辉,叶小卫.基于NetFlow的网络异常流量检测[J].微计算机应用,2007,28(7):709-713. 被引量:7
  • 3HEBERLEIN L,DIAS G V,LEVITT K N,et al.A network security monitor[C] // Proceedings of the IEEE Computer Society Symposium.Research in Security and Privacy.New York:IEEE,1990:296-304.
  • 4MAHONEY V M.A machine learning approach to detecting attacks by identifying anomalies in network traffic[D].Melbourne:Florida Institute of Technology,2003.
  • 5HAWKINS D M,QUI P,KANG C W.The change point model for statistical process control[J].Journal of Quality Technology,2003,35(4):355-366.
  • 6BARFORD P,KLINE J,PLONKA D,et al.A signal analysis of network traffic anomalies[C] // Proceedings of ACM SIGCOMM Internet Measurement Workshop.New York:ACM,2002:71-82.
  • 7KULLBACK S,LEIBLER R A.On information and sufficiency[J].Annals of Mathematical Statistics,1951,22(1):79-86.
  • 8PORRAS P A,NEUMANN P G.EMERALD:Event monitoring enabling responses to anomalous live disturbances[EB/OL].[2009-08-21].http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.114.4122.
  • 9Mirkovic J, Reiher P. A Taxonomy of DDoS attack and DDoS defense mechanisms [J] ACM SIG- COMM Computer Communications Review, 2004, 34(2) : 39-53.
  • 10Lawniczak A T, Wu H, Di Stefan B N. Detection of anomalous packet traffic via entropy[C] // Proceed ings of the 22nd IEEE Canadian Conference on Elec trical and Computer Engineering, Canada, 2009: 137-141.

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