International Journal of Computer
Trends and Technology

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Volume 4 | Issue 4 | Year 2013 | Article Id. IJCTT-V4I4P121 | DOI : https://doi.org/10.14445/22312803/IJCTT-V4I4P121

False Data Detection Using MAC pairs in Wireless Sensor Networks

V.M.Sivagami, K.S.Easwara Kumar

Citation :

V.M.Sivagami, K.S.Easwara Kumar, "False Data Detection Using MAC pairs in Wireless Sensor Networks," International Journal of Computer Trends and Technology (IJCTT), vol. 4, no. 4, pp. 539-545, 2013. Crossref, https://doi.org/10.14445/22312803/IJCTT-V4I4P121

Abstract

Wireless sensor networks are vulnerable to many types of security attacks, including false data injection, data forgery, and eavesdropping. Sensor nodes can be compromised by intruders, and the compromised nodes can distort data integrity by injecting false data. False data can be injected by compromised sensor nodes in various ways, including data aggregation and relaying. Data confidentiality prefers data to be encrypted at the source node and decrypted at the destination. However, data aggregation techniques usually require any encrypted sensor data to be decrypted at data aggregators for aggregation. The basic idea behind the false data detection algorithm is to form pairs of sensor nodes such that one pair computes a message authentication code (MAC) of forwarded data and the other pair mate later verifies the data using the MAC. Data aggregation is implemented in wireless sensor networks to eliminate data redundancy, reduce data transmission, and improve data accuracy.

Keywords

Data aggregation and authentication protocol (DAA), Data integrity, network-level security, Message Authentication Code(MAC) and Sensor networks.

References

[1] Suat Ozdemir, Member, IEEE, and Hasan Çam, Senior Member, IEEE, ” Integration of False Data Detection With Data Aggregation and Confidential Transmission in Wireless Networks”,Vol.18,no.3,June 2010.  Sensor
[2] Z. Yu and Y. Guan, “A dynamic en-route scheme for filtering false data in wireless sensor networks,” in Proc. IEEE INFOCOM, Barcelona, Spain, Apr. 23–27, 2006, pp. 1–12.
[3] R. Rajagopalan and P. K. Varshney, “Data aggregation techniques in sensor networks: A survey,” IEEE Commun. Surveys Tutorials, vol. 8, no. 4, 4th Quarter 2006.
[4] W. Du, J. Deng, Y. S. Han, and P. K. Varshney, “A witness-based approach for data fusion assurance in wireless sensor networks,” in Proc. IEEE GLOBECOM, 2003, pp. 1435–1439.
[5] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A survey on sensor networks,” IEEE Commun. Mag., vol. 40, no. 8, pp. 102–114, Aug. 2002.
[6] M. Sivrianosh, D.Westhoff, F. Armknecht, and J. Girao, “Non-manipulable aggregator node election protocols for wireless sensor networks,” in Proc. IEEE WiOpt, Cyprus, Apr. 2007, pp. 1–10.
[7] F. Ye, H. Luo, S. Lu, and L. Zhang, “Statistical en-route detection and filtering of injected false data in sensor networks,” in Proc. IEEE INFOCOM, 2004, vol. 4, pp. 2446–2457.
[8] S. Zhu, S. Setia, S. Jajodia, and P. Ning, “Interleaved hop-by-hop authentication against false data injection attacks in sensor networks,” ACM Trans. Sensor Netw., vol. 3, no. 3, Aug. 2007.
[9] H. Yang and S. Lu, “Commutative cipher based en-route filtering in wireless sensor networks,” in Proc. IEEE VTC, 2004, vol. 2, pp.1223–1227.
[10] D. Seetharam and S. Rhee, “An efficient pseudo random number generator for low-power sensor networks,” in Proc. 29th Annu. IEEE Int.Conf. Local Comput. Netw., 2004, pp. 560–562.