期刊文献+

传感器网络中一种基于地理位置的虚假数据过滤方案 被引量:5

Geographical information based false report filtering scheme in wireless sensor networks
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摘要 提出了一种基于地理位置的虚假数据过滤方案GFFS。在GFFS中,节点在部署后将地理位置预分发给部分其他节点存储,每个数据报告必须包含t个具有不同密钥分区检测节点的MAC以及地理位置,转发节点既对数据分组中包含的MAC和地理位置的正确性进行验证,还对地理位置的合法性进行验证。理论分析及仿真实验表明,GFFS能有效地过滤不同地理区域的多个妥协节点协同伪造的虚假数据,且具备远强于已有方案的妥协容忍能力。 A geographical information based false reports filtering scheme (GFFS) in sensor networks was presented. In GFFS, each node distributes its location information to some other nodes after deployment. When a report was generated for an observed event, it must carry not only MACs from t detecting nodes with distinct key partitions, but also locations of these nodes. Each forwarding node checks not only the correctness of the MAC and the locations carried in the report, but also the legitimacy of the locations. Analysis and simulation results demonstrate that GFFS can resist collaborative false data injection attacks and thus can tolerate much more compromised nodes than existing schemes.
出处 《通信学报》 EI CSCD 北大核心 2012年第2期156-163,共8页 Journal on Communications
关键词 无线传感器网络 虚假数据过滤 妥协节点:协同攻击 wireless sensor network false report filtering compromised node collaborative attack
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参考文献15

  • 1任丰原,黄海宁,林闯.无线传感器网络[J].软件学报,2003,14(7):1282-1291. 被引量:1712
  • 2苏忠,林闯,封富君,任丰原.无线传感器网络密钥管理的方案和协议[J].软件学报,2007,18(5):1218-1231. 被引量:111
  • 3YE F, LUO H, ZHANG L. Statistical en-route filtering of injected false data in sensor networks[A]. Proceedings of 23th Annual Joint Conference of the IEEE Computer and Communications Societies, INFOCOM'04[C]. Hong Kong, China, 2004.2446-2457.
  • 4ZHU S, SETIA S, JAJODIA S. An interleaved hop-by-hop authentication scheme for filtering of injected false data in sensor networks[A]. Proceeding IEEE Symposium on Security and Privacy, S&P'04[C]. Berkley, CA, USA, 2004.259-271.
  • 5YU Z, GUAN Y. A Dynamic en-route scheme for filtering false data injection in wireless sensor networks[A]. Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, SenSys'05[C]. San Die~o, 2005.294-295.
  • 6LIE W J. A probabilistic voting-based filtering scheme in wireless sensor networks[A]. Proceedings of the International Wireless Communications and Mobile Computing Conference, IWCMC'06[C]. Vancouver, Canada, 2006.255-265.
  • 7MA M. Resilience of sink filtering scheme in wireless sensor networks[J]. Computer Communications, 2006, 30(1):55-65.
  • 8YANG H, LU S. Commutative cipher based en-route filtering in wireless sensor networks[A]. Vehicular Technology Conference, VTC'04[C]. Los Angeles, USA, 2004.1223-1227.
  • 9WANG H, LI Q. PDF: a public-key based false data filtering scheme in sensor networks[A]. Proceedings of the International Conference on Wireless Algorithms, Systems and Applications, WASA'07[C]. Vaasa, Finland, 2007.129-138.
  • 10REN K, LOU W, ZHANG Y. Providing location-aware end-to-end data security in wireless sensor networks[A]. Proceedings of the IEEE Conference on Computing and Communicating, INFOCOM'06[C]. Barcelona, Spain, 2006.585-598.

二级参考文献51

  • 1Arora A, Dutta P, Bapat S, Kulathumani V. A line in the sand: A wireless sensor network for target detection, classification, and tracking. Computer Networks, 2004, 46(5): 605-634.
  • 2Gandhi S, Suri S, Welzl E. Catching elephants with mice: Sparse sampling for monitoring sensor networks. In Proc. the 5th International Conference on Embedded Networked Sensor Systems (SenSys2007), Sydney, Australia, July 18-21, 2007, pp.601-616.
  • 3Tolle G, Polastre J, Szewczyk R, Culler D. A macroscope in the redwoods. In Proc. the 3rd International Conference on Embedded Networked Sensor Systems (SenSys 2005), San Diego, USA, July 18-21, 2005, pp.101--110.
  • 4Govindarajulu Z. Elements of Sampling Theory and Methods. New York: Prentice Hall, 1999.
  • 5Funke S. Topological hole detection in wireless sensor networks and its applications. In Pvoc. DIALM-POMC 2005, Cologne, Germary, July 18- 21, 2005, pp.50-61.
  • 6Hsu C-S, Sheu J-P, Chang Y-J. Efficient broadcasting protocols for regular wireless sensor networks. Wireless Communications and Mobile Computing, 2006, 6(1): 35-48.
  • 7Dimakis A G, Sarwate A D, Wainwright M J. Geographic gossip: Efficient aggregation for sensor networks. In Proc. IPSN 2006, Nashville, USA, Jul. 15 20, 2006, pp.1-10.
  • 8Kempe D, Dobra A, Gehrke J. Gossip-based computation of aggregate information. In Proc. FOCS2003, Cambridge, USA, Feb. 14-17, 2003, pp,1 -10.
  • 9Massoulie L, Merrer E L, Kermarrec A, Ganesh A. Peer counting and sampling in overlay networks: Random walk methods. In Proc. PODC2006, Denver, USA, July 23-26, 2006, pp.211-222.
  • 10Wang Y, Gao J, Mitchell J. Boundary recognition in sensor networks by topological methods. In Proc. MOBICOM2006, Los Angeles, USA, Sept. 18-21, 2006, pp.56- 168.

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