Credible Secure Data Aggregation in Wireless Sensor Networks

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 324)

Abstract

Wireless sensor networks contain large number of low-cost sensor devices called nodes that have severely limited in sensing, computation, and communication abilities. In order to improve the sensor network lifetime, the amount of data transmission minimization is a vital issue. Data aggregation is the technique which is used to minimize the rate of data transmission among the sensor networks. Data aggregation is the process of merging sensor data in order to moderate the quantity of data transmission in the network. The results of data aggregation are typically used to make serious decisions; hence, the correctness of final aggregation results is very important. In this paper, credible-based secure data aggregation (CDA) is proposed to ensure the quality of data aggregation. The main idea of this scheme is that secured, accurate data aggregation is achieved based on the credible value of the sensor nodes. The simulation results show that protocol CDA considerably expands the system reliability through secured data aggregation in the occurrence of compromised nodes.

Keywords

Credibility Data aggregation Wireless sensor networks 

References

  1. 1.
    I.F. Akyildiz, I.H Kasimoglu, Wireless sensor and actor networks: research challenges. Ad Hoc Netw. (2004) pp. 351–367Google Scholar
  2. 2.
    G. Pottie, W. Kaiser, Wireless integrated network sensors. Commun. ACM 43(5), 51–58 (2000)CrossRefGoogle Scholar
  3. 3.
    V. Mhatre et al., Design guidelines for wireless sensor networks: communication, clustering and aggregation. Ad Hoc Netw. J 2(1), 45–63 (2004). Elsevier ScienceCrossRefGoogle Scholar
  4. 4.
    E. Stavrou, A. Pitsillides, A survey on secure multipath routing protocols in WSN’s. Comput. Network. 54, 2215–2238 (2010)CrossRefMATHGoogle Scholar
  5. 5.
    O. Cheikhrouhouet al., LNT: a Logical neighbor tree for secure group management in wireless sensor networks. Procedia Comput. Sci. (2011) pp. 1877–0509Google Scholar
  6. 6.
    C. Intanagon Wiwat, D. Estrin, R. Govindan, J. Heidemann, Impact of network density on data aggregation in wireless sensor networks, in Proceedings International Conference on Distributed Computing Systems. (2002) pp. 457–458 Google Scholar
  7. 7.
    M. Ding, X. Cheng, G. Xue, Aggregation tree construction in sensor networks. IEEE Xplore (2003) 7803-7954-3/03Google Scholar
  8. 8.
    Hongjuan Li, Kai Lin, K. Li, Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks. Comput. Commun. 34, 591–597 (2011)CrossRefGoogle Scholar
  9. 9.
    S. Ozdemir, Functional reputation based reliable data aggregation and transmission for wireless sensor networks. Comput. Commun. 31, 3941–3953 (2008)Google Scholar
  10. 10.
    K. Lu, L. Huang, Y. Wan, H. Xu, Energy-efficient data gathering in large wireless sensor networks, in Second International Conference on Embedded Software and Systems. (2005) pp. 5–10Google Scholar
  11. 11.
    S. Ozdemir, Y. Xiao, Secure data aggregation in wireless sensor networks: A comprehensive overview. Comput. Netw. 53, 2022–2037 (2009)Google Scholar
  12. 12.
    R. Roman, C. Alcaraz, J. Lopez, A survey of cryptographic primitives and implementations for hardware-constrained sensor network nodes, Mob. Netw. (2007) pp. 231–244Google Scholar
  13. 13.
    H. Sethi, R.B. Patel, EIRDA: an energy efficient interest based reliable data aggregation protocol for wireless sensor networks. Int. J. Comput. Appl. 22(7), 0975–8887 (2011)Google Scholar
  14. 14.
    E. Fasolo, M. Rossi, J. Widmer, M. Zorzi, In-network aggregation techniques for wireless sensor networks: a survey. IEEE Wirel. Comm. 14(2), 70–87 (2007)CrossRefGoogle Scholar
  15. 15.
    L.A. Villas, A. Boukerche, R.B. Araujo, A.A. Loureiro, A Reliable and Data Aggregation Aware Routing Protocol for Wireless Sensor Networks, in Proceedings 12th ACM Int’l Conference Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM). pp. 245–252Google Scholar
  16. 16.
    P. SudipMisra, D. Thomasinous, A simple, least-time, and energy-efficient routing protocol with one-level data Aggregation for wireless sensor networks. J. Syst. Softw. 83, 852–860 (2010)CrossRefGoogle Scholar
  17. 17.
    L. Villas, A. Boukerche, R.B de Araujo, A.A.F. Loureiro, Highly dynamic routing protocol for data aggregation in sensor networks, in Proceedings IEEE Symposium Computers and Communication (ISCC). (2010) pp. 496–502Google Scholar
  18. 18.
    L.A. Villas, A. Boukerche, H.S. Ramos, A.B.F de Oliveira, R.B. de Araujo, A.A.F. Loureiro. DRINA: A lightweight and reliable routing approach for in-network aggregation in wireless sensor networks. IEEE Trans Comput. 62(4) (2013)Google Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.School of Computer Science, Engineering and ApplicationsBharathidasan UniversityTiruchirapalliIndia

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