Skip to main content
SpringerLink
Log in

Dropping False Packet to Increase the Network Lifetime of Wireless Sensor Network using EFDD Protocol

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In Wireless Sensor Network (WSN) sensors are densely deployed where the intruders can compromise some sensor nodes and inject false data in order to raise false alarms, reduce network lifetime, utilize bandwidth resources and so on. False Data Injection can possibly occur in Data Aggregation (DA) and Data Forwarding (DF). This paper analyses EFDD Protocol-Early False Data Detection Protocol which addresses the two possibilities in a simple and secure way considering the constraints of sensor nodes. The main idea is the selection of the network structure; this protocol will work effectively in Spatial/Semantic Correlation Tree Structure (SCT). False Data Detection in DA is done using some monitoring nodes which will monitor the Data Aggregator. EFDD in SCT structure reduce the counterfeit data transmission when compared to other structure in a better way. The result shows that EFDD reduce data transmission by dropping false data earlier and it also reduces computation when compared to the existing schemes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Bojkovic Z.S., Bakmaz B.M., Bakmaz M.R. (2008) Security issues in wireless sensor network. Intenational Journal of Commnications 2(1): 106–115

    Google Scholar 

  2. Krishnamachari, B., Estrin, D., & Wicker, S. (2002). Impact on Data Aggregation in wireless sensor network. Distributed Computing Systems Workshops. (DEBS), Vienna, Austria.

  3. Zhu Y., Vedantham R., Park S.-J., Sivakumar R. (2008) A scalable correlation aware aggregation strategy for wireless sensor networks. Journal Information fusion archive 9(3): 354–369

    Article  Google Scholar 

  4. Ye F., Luo H., Lu S., Zhang L. (2005) Statistical en-route detection and filtering of injected false data in sensor networks. IEEE Journal of Selected Areas in Communications 23(4): 839–850

    Article  Google Scholar 

  5. Yu, Z., & Guan, Y. (2006). A dynamic en-route scheme for filtering false data in wireless sensor networks. In Proceedings of the IEEE INFOCOM, pp. 1–12, Barcelona, Spain, April 23–27.

  6. Hu, L., Evans, D. (2003). Secure aggregation for wireless networks. In Proceedings of the workshop security assurance Ad hoc networks, pp. 384–394, Orlando, FL, January 28.

  7. Du, W., Deng, J., Han, Y. S., & Varshney, P. K. (2003). A witness-based approach for data fusion assurance in wireless sensor networks. In Proceedings of the IEEE GLOBECOM, pp. 1435–1439.

  8. Przydatek, B., Song, D., & Perrig, A. (2003). SIA: Secure information aggregation in sensor networks. In Proceedings of the SenSystems, pp. 255–265.

  9. Çam H., Ozdemir S., Nair P., Muthuavinashiappan D., Sanli H. O. (2006) Energy-efficient and secure pattern based data aggregation for wireless sensor networks. Computer Communications 29(4): 446–455

    Article  Google Scholar 

  10. Shu J., Chen Y., Liu L., Zhang S., Li J. (2010) Study on aggregation tree construction based on GRID. Journal of Computers 5(6): 852–860

    Article  Google Scholar 

  11. Rivest, R. L. (1994). The RC5 encryption algorithm. In Proceedings of the 2nd international workshop FSE, pp. 86–96.

  12. http://www.faqs.org/rfcs/rfc1321.html.

  13. Manoj, R., & Dhinakaran, N. Survey of key predistribution schemes for key management in wireless sensor networks. ICNVS’10 Proceedings of the 12th international conference on Networking, VLSI and Signal Processing, 135–140.

  14. http://www.select.cs.cmu.edu/data/index.html.

  15. Ozdemir S., Çam H. (2010) Integration of false data detection with data aggregation and confidential transmission in wireless sensor networks. IEEE/ACM Transactions on Networking 18(3): 736–749

    Article  Google Scholar 

  16. Ding M., Cheng X., Xue G. (2003) Aggregation tree construction in sensor network. IEEE 58th Vehicular Technology Conference 4: 2168–2172

    Google Scholar 

  17. Preda R.O., Vizireanu D.N. (2011) A robust wavelet based video watermarking scheme for copyright protection using the human visual system. Journal of Electronic Imaging 20: 013022

    Article  Google Scholar 

  18. Sandhya M. K., Murugan K. (2011) Secure data aggregation in wireless sensor networks using privacy homomorphism. Journal of Advances in Networks and Communications 132(2): 482–490

    Article  Google Scholar 

  19. Preda R. O., Vizireanu D. N. (2011) Quantization based video watermarking in the wavelet domain with spatial and temporal redundancy. International Journal of Electronics 98(03): 393–405

    Article  Google Scholar 

  20. Preda R. O., Vizireanu D. N. (2010) A robust digital watermarking scheme for video copyright protection in the wavelet domain. Measurement 43(10): 1720–1726

    Article  Google Scholar 

  21. Lee H. Y., Cho T. H., Kim H.-J. (2010) Fuzzy-based detection of injected false data in wireless sensor networks. Journal of Information Security and Assurance 76: 128–137

    Article  Google Scholar 

  22. Tan H. O., Korpeoglu I., Stojmenovic I. (2011) Computing localized power—efficient data aggregation trees for sensor networks. Journal of Parallel and Distributed Systems–IEEE 22(3): 489–500

    Article  Google Scholar 

  23. Zhu Y., Vedantham R., Park S.-J., Sivakumar R. (2008) A scalable correlation aware aggregation strategy for wireless sensor networks. ACM Journal of Information Fusion 9(3): 354–369

    Article  Google Scholar 

  24. Zhu, S., Setia, S., Jajodia, S., & Ning, P. (2007). Interleaved hop-by-hop authentication against false data injection attacks in sensor networks. Journal ACM Transactions on Sensor Networks, 3(3), Article no: 14.

    Google Scholar 

  25. Dsoul, M., Al-Khasawneh, A., Abdallah, A. E., & Obeidat, I. (2012). An energy threhold-based clustering protocol for wireless sensor networks. Journal of Wireless personal Communications, pp. 1–14.

  26. Gao T., Jin R. C., Song J. y., Xu T. B., Wang L. D. (2012) Energy-efficient cluster head selection scheme based on multiple criteria decision making for wireless sensor networks. Journal of Wireless personal Communications 63(4): 871–894

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Technology, Karunya University, Coimbatore, Tamil Nadu, India

    S. Manoj Kumar

  2. Department of Computer Science & Engineering, Sri Ramakrishna Engineering College, Coimbatore, Tamil Nadu, India

    N. Rajkumar

  3. WIPRO Technologies, Chennai, India

    W. Catherine Christinal Mary

Authors
  1. S. Manoj Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. Rajkumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. W. Catherine Christinal Mary
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. Manoj Kumar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Manoj Kumar, S., Rajkumar, N. & Catherine Christinal Mary, W. Dropping False Packet to Increase the Network Lifetime of Wireless Sensor Network using EFDD Protocol. Wireless Pers Commun 70, 1697–1709 (2013). https://doi.org/10.1007/s11277-012-0775-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-012-0775-3

Keywords

Search

Navigation