Study & Design of Advanced Data Aggregation technique in Wireless Sensor Networks

In today’s fast growing technology, most of the applications uses Wireless Sensor Networks(WSN) and it plays the important role to achieve the required results. The important objective while designing the WSN is to maintain the data privacy, so that neighboring nodes should not be able to get the private data and also implementing the efficient data aggregation techniques to achieve better performance in privacy preservation, less communication overhead and accuracy in intermediate data aggregation. In this paper two privacy preserving data aggregation techniques are discussed namely Cluster Based Privacy Data Aggregation(CPDA) and Slice-Mix-AggRegaTe (SMART). CPDA will have an advantage of better privacy preservation and also less communication overhead. In SMART, better privacy preservation can be achieved but there is a communication

[1]  Wenliang Du,et al.  Deriving private information from randomized data , 2005, SIGMOD '05.

[2]  Joseph Y. Halpern,et al.  Ra-tional secret sharing and multiparty computation , 2004, STOC 2004.

[3]  Deborah Estrin,et al.  A wireless sensor network For structural monitoring , 2004, SenSys '04.

[4]  Deborah Estrin,et al.  Impact of network density on data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems.

[5]  Srinivasan Seshan,et al.  Cache-and-query for wide area sensor databases , 2003, SIGMOD '03.

[6]  C. Castelluccia,et al.  Efficient aggregation of encrypted data in wireless sensor networks , 2005, The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services.

[7]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[8]  Deborah Estrin,et al.  Directed diffusion: a scalable and robust communication paradigm for sensor networks , 2000, MobiCom '00.

[9]  Alexandre V. Evfimievski,et al.  Privacy preserving mining of association rules , 2002, Inf. Syst..

[10]  Qi Wang,et al.  On the privacy preserving properties of random data perturbation techniques , 2003, Third IEEE International Conference on Data Mining.

[11]  Yehuda Lindell,et al.  Privacy Preserving Data Mining , 2002, Journal of Cryptology.

[12]  Donggang Liu,et al.  Establishing pairwise keys in distributed sensor networks , 2005, TSEC.

[13]  Katia Obraczka,et al.  The impact of timing in data aggregation for sensor networks , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[14]  Virgil D. Gligor,et al.  A key-management scheme for distributed sensor networks , 2002, CCS '02.

[15]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[16]  Mark G. Terwilliger,et al.  Overview of Sensor Networks , 2004 .

[17]  Jianliang Xu,et al.  Extending Network Lifetime for Precision-Constrained Data Aggregation in Wireless Sensor Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[18]  Ivan Damgård,et al.  On the complexity of verifiable secret sharing and multiparty computation , 2000, STOC '00.

[19]  Helen J. Wang,et al.  Privacy-Preserving Friends Troubleshooting Network , 2005, NDSS.

[20]  Dirk Westhoff,et al.  CDA: concealed data aggregation for reverse multicast traffic in wireless sensor networks , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.

[21]  Andrew Chi-Chih Yao,et al.  Protocols for secure computations , 1982, FOCS 1982.