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  • 标题:A Secure and Efficient Data Aggregation Framework in Vehicular Sensing Networks
  • 本地全文:下载
  • 作者:Suguo Du ; Peng Tian ; Kaoru Ota
  • 期刊名称:International Journal of Distributed Sensor Networks
  • 印刷版ISSN:1550-1329
  • 电子版ISSN:1550-1477
  • 出版年度:2013
  • 卷号:2013
  • DOI:10.1155/2013/298059
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Vehicular ad hoc networks support a wide range of promising applications including vehicular sensing networks, which enable vehicles to cooperatively collect and transmit the aggregated traffic data for the purpose of traffic monitoring. The reported literatures mainly focus on how to achieve the data aggregation in dynamic vehicular environment, while the security issue especially on the authenticity and integrity of aggregation results receives less attention. In this study, we introduce a basic aggregation scheme which could aggregate the data and the message authentication codes by using syntactic aggregation and cryptographic aggregation. To tolerate duplicate messages and further improve the aggregation performance, we introduce a secure probabilistic data aggregation scheme based on Flajolet-Martin sketch and sketch proof technique. We also discuss the tradeoff between the bandwidth efficiency and the estimation accuracy. Extensive simulations and analysis demonstrate the efficiency and effectiveness of the proposed scheme.
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