无线传感器网络中面向多数据查询的安全数据融合算法
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摘要
安全数据融合方案在分布式应用程序中得到了广泛的应用,例如无线传感器网络,来降低通信成本,延长网络生命周期并提供安全等。然而,大多数安全数据融合方案仅适用于单一类型的统计数据(例如:基于求和或基于比较的统计数据),并且不适用于获得多个统计结果。提出了一种基于同态加密的多函数安全数据融合方案(HMDA),本方案在映射阶段和编码阶段提供数据保护和顺序保护,以及满足任意统计数据查询。该算法能够预防多种类型的攻击,保证网络负载均衡,且不存在明显的瓶颈。理论分析和实验结果表明,HMDA高的精确度,同时减少网络流量。
Secure data aggregation schemes are widely used in distributed applications,such as wireless sensor networks,to reduce communication costs,prolong network lifecycle,and provide security.However,most secure data aggregation schemes apply only to a single type of statistics(for example,based on sum or comparison based statistics)and do not apply to obtaining multiple statistical results. In this paper, a multi-function secure data aggregation scheme(HMDA) based on Homomorphic encryption is proposed,which provides data protection and sequential protection in the mapping phase and coding phase,and satisfies arbitrary statistic data query. This algorithm can prevent many kinds of attacks,guarantee Network load balance,and there is no obvious bottleneck. Theoretical analysis and experimental results show that the HMDA algorithm can ensure that the data aggregation results meet the high accuracy and reduce the network traffic.
Secure data aggregation schemes are widely used in distributed applications,such as wireless sensor networks,to reduce communication costs,prolong network lifecycle,and provide security.However,most secure data aggregation schemes apply only to a single type of statistics(for example,based on sum or comparison based statistics)and do not apply to obtaining multiple statistical results. In this paper, a multi-function secure data aggregation scheme(HMDA) based on Homomorphic encryption is proposed,which provides data protection and sequential protection in the mapping phase and coding phase,and satisfies arbitrary statistic data query. This algorithm can prevent many kinds of attacks,guarantee Network load balance,and there is no obvious bottleneck. Theoretical analysis and experimental results show that the HMDA algorithm can ensure that the data aggregation results meet the high accuracy and reduce the network traffic.
引文
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[13]Chen L,Lu R,Cao Z,et al. Multifunctional data aggregation in privacy-preserving smart grid communications. Peer-to-Peer Netw,2015(8):777-792.
[14]Mykletun E,Girao J,Westhoff D. Public key based cryptoschemes for data concealment in wireless sensor networks[C]. In Proceedings of the 2006IEEE International Conference on Communications,Istanbul,2006(5):2288-2295.
[15]NOAA. Tropical Atmosphere Ocean(TAO)Project.Available online[EB/OL]. http://www.pmel.noaa.gov/tao(accessed on 21 April 2016.)
[16]杨函.基于无线传感器的普适计算系统安全性探讨[J].电子科技,2018(4):33-35.
[17]杨阿弟,佘明辉.无线传感器网络中移动目标的定位及误差分析[J].西安工业大学学报,2016(4):340-344.
[18]张希洋,曹国强,梁峰,等.基于单片机控制的嵌入式智能无线传感器设计[J].现代电子技术,2017(13):80-82.
[2]苘大鹏,王臣业,杨武,等.低能耗的无线传感器网络隐私数据融合方法[J].清华大学学报:自然科学版,2017(2):213-219.
[3]杨树杰.面向网络化系统的分布式估计及优化算法研究[D].北京:北京邮电大学,2017.
[4]赵丹,杨庚.一种基于复数域的数据融合完整性保护算法[J].计算机技术与发展,2012,22(8):150-154.
[5] Yang,G.;Li,S.;Xu,X.;Dai,H.;Yang,Z. Precision-enhanced and encryption-mixed privacypreserving data aggregation in wireless sensor networks[J]. Int. J. Distrib. Sens. Netw,2013,427275.
[6]邵莉莉.无线传感器网络中基于同态加密的安全数据融合技术研究[D].合肥:安徽大学,2017.
[7] Ozdemir S,Xiao Y. Secure data aggregation in wireless sensor networks:A comprehensive overview Comput[J]. Net. 2009(53):2022-2037.
[8] Castelluccia C,Chan A C F,Mykletun E,et al.Efficient and provably secure aggregation of encrypted data in wireless sensor networks[J].ACM Trans. Sens. Netw. 2009(5):1-36.
[9] Rivest R L,Adleman L,Dertouzos M L. On data banks and privacy homomorphisms[J]. Found Secur Comput,1978(4):169-180.
[10]Acharya M,Girao J,Westhoff D. Secure comparison of encrypted data in wireless sensor networks[J].In Proceedings of the Third International Symposium on Modeling and Optimization in Mobile,Ad Hoc,and Wireless Networks(WiOpt’05),Trentino,Italy,2005:47-53.
[11]Agrawal R,Kiernan J,Srikant R,et al. Order preserving encryption for numeric data[J]. In Proceedings ofthe 2004 ACM SIGMOD International Conference on Management of Data,Paris,France,2004:563-574.
[12]Ertaul L,Kedlaya V. Computing Aggregation Function Minimum/Maximum using Homomorphic Encryption Schemes in Wireless Sensor Networks[C].In Proceedings of the 2007 International Conference on Wireless Networks,Las Vegas,NV,2007:186-192.
[13]Chen L,Lu R,Cao Z,et al. Multifunctional data aggregation in privacy-preserving smart grid communications. Peer-to-Peer Netw,2015(8):777-792.
[14]Mykletun E,Girao J,Westhoff D. Public key based cryptoschemes for data concealment in wireless sensor networks[C]. In Proceedings of the 2006IEEE International Conference on Communications,Istanbul,2006(5):2288-2295.
[15]NOAA. Tropical Atmosphere Ocean(TAO)Project.Available online[EB/OL]. http://www.pmel.noaa.gov/tao(accessed on 21 April 2016.)
[16]杨函.基于无线传感器的普适计算系统安全性探讨[J].电子科技,2018(4):33-35.
[17]杨阿弟,佘明辉.无线传感器网络中移动目标的定位及误差分析[J].西安工业大学学报,2016(4):340-344.
[18]张希洋,曹国强,梁峰,等.基于单片机控制的嵌入式智能无线传感器设计[J].现代电子技术,2017(13):80-82.