A Novel Framework for Abnormal Behaviour Identification and Detection for Wireless Sensor Networks
Despite extensive study on wireless sensor network
security, defending internal attacks and finding abnormal behaviour
of the sensor are still difficult and unsolved task. The conventional
cryptographic technique does not give the robust security or detection
process to save the network from internal attacker that cause by
abnormal behavior. The insider attacker or abnormally behaved
sensor identificationand location detection framework using false
massage detection and Time difference of Arrival (TDoA) is
presented in this paper. It has been shown that the new framework
can efficiently identify and detect the insider attacker location so that
the attacker can be reprogrammed or subside from the network to
save from internal attack.
[1] Y. Zhou, Y. Fang, and Y. Zhang, "Securing wireless sensor networks: a
survey," IEEE Communications Surveys & Tutorials, 3rd Quarter 2008.
[2] W. T. Zhu, Y. Xiang, J. Zhou, R. H. Deng, and F.Bao, "Secure
localization with attack detection in wireless sensor networks,"
International Journal of Information Security, vol. 10, no. 3, pp. 155-
171, 2011.
[3] A. Srinivasan, and J. Wu, "A Survey on Secure Localization in Wireless
Sensor Networks," Encyclopedia of wireless and mobile
communications, 2008.
[4] L. Lazos, and R. Poovendran, "SeRLoc: Secure range independent
localization for wireless sensor networks," in ACM workshop on
Wireless security (ACMWiSe -04), Philadelphia, 2004.
[5] L. Lazos and R. Poovendran, "HiRLoc: High-Resolution Robust
Localization for Wireless Sensor Networks," IEEE Journal on Selected
Areas in Communications, vol. 24, no. 2, February 2006.
[6] D. Liu, P. Ning, and W. Du, "Attack-Resistant Location Estimation in
Sensor Networks," in Proc. of The Fourth International Conference on
InformationProcessing in Sensor Networks (IPSN -05), 2005, pp. 99-
106.
[7] S. Capkun and J.-P.Hubaux, "Secure positioning of wireless devices
with application to sensor networks," in Proc. of IEEE INFOCOM -05,
2005.
[8] Y. Zhang, W. Yang, K. Kim, and M. Park, "Inside attacker detection in
Hierarchical Wireless Sensor Networks," in Proc. of the 3rd
International conference on innovative computing information and
control (ICICIC), 2008.
[9] C. Haiguang, C, XinHua, and N. Junyu, "Implicit Security
Authentication Scheme in Wireless Sensor Networks," in Proc. of 2010
International Conference on Multimedia Information Networking and
Security, 2010.
[10] Y. Chraibi, "Localization in wireless sensor networks," Masters- degree
project submitted to KTH signal and sensor systems, Stockholm,
Sweden, 2005.
[11] X. Xiaochun, R. Nageswara, and S. Sartaj, "A computational geometry
method for DTOA triangulation," in Proc, of 10th International
Conference on Information Fusion, 2007, pp. 1-7.
[12] W. H. Foy, "Position-Location Solutions by Taylor-Series Estimation,"
IEEE Transactions on Aerospace and Electronic Systems, vol. AES-12,
pp. 187-194, March 1976.
[13] D. J. Torrieri, "Statistical Theory of Passive Location Systems," IEEE
Transactions on Aerospace and Electronic Systems, vol. AES-20, no. 2,
pp. 183-198, March 1984.
[14] B. Friedlander, "A Passive Localization Algorithm and Its Accuracy
Analysis," IEEE Journal of Oceanic Engineering, vol. OE-12, no. 1, pp.
234-244, January 1987.
[15] H. C. Schau, and A. Z. Robinson, "Passive Source Localization
Employing Intersecting Spherical Surfaces from Time-of-Arrival
Differences," IEEE Transactions on Acoustics, Speech, and Signal
Processing, vol. ASSP-35, no. 8, pp. 1223-1225, August 1987.
[16] J. O. Smith, and J. S. Abel, "The Spherical Interpolation Method for
Source Localization," IEEE Journal of Oceanic Engineering, vol. OE-
12, no. 1, pp. 246-252, January 1987.
[17] J. S. Abel and J. O. Smith, "The Spherical Interpolation Method for
Closed-Form Passive Localization Using Range Difference
Measurements," in Proc. ICASSP-87, Dallas, TX, 1987, pp. 471-474.
[18] Y. T. Chan and K. C. Ho, "A Simple and Efficient Estimator for
Hyperbolic Location," IEEE Transactions on Signal Processing, vol. 42,
no. 8, pp. 1905-1915, August 1994.
[1] Y. Zhou, Y. Fang, and Y. Zhang, "Securing wireless sensor networks: a
survey," IEEE Communications Surveys & Tutorials, 3rd Quarter 2008.
[2] W. T. Zhu, Y. Xiang, J. Zhou, R. H. Deng, and F.Bao, "Secure
localization with attack detection in wireless sensor networks,"
International Journal of Information Security, vol. 10, no. 3, pp. 155-
171, 2011.
[3] A. Srinivasan, and J. Wu, "A Survey on Secure Localization in Wireless
Sensor Networks," Encyclopedia of wireless and mobile
communications, 2008.
[4] L. Lazos, and R. Poovendran, "SeRLoc: Secure range independent
localization for wireless sensor networks," in ACM workshop on
Wireless security (ACMWiSe -04), Philadelphia, 2004.
[5] L. Lazos and R. Poovendran, "HiRLoc: High-Resolution Robust
Localization for Wireless Sensor Networks," IEEE Journal on Selected
Areas in Communications, vol. 24, no. 2, February 2006.
[6] D. Liu, P. Ning, and W. Du, "Attack-Resistant Location Estimation in
Sensor Networks," in Proc. of The Fourth International Conference on
InformationProcessing in Sensor Networks (IPSN -05), 2005, pp. 99-
106.
[7] S. Capkun and J.-P.Hubaux, "Secure positioning of wireless devices
with application to sensor networks," in Proc. of IEEE INFOCOM -05,
2005.
[8] Y. Zhang, W. Yang, K. Kim, and M. Park, "Inside attacker detection in
Hierarchical Wireless Sensor Networks," in Proc. of the 3rd
International conference on innovative computing information and
control (ICICIC), 2008.
[9] C. Haiguang, C, XinHua, and N. Junyu, "Implicit Security
Authentication Scheme in Wireless Sensor Networks," in Proc. of 2010
International Conference on Multimedia Information Networking and
Security, 2010.
[10] Y. Chraibi, "Localization in wireless sensor networks," Masters- degree
project submitted to KTH signal and sensor systems, Stockholm,
Sweden, 2005.
[11] X. Xiaochun, R. Nageswara, and S. Sartaj, "A computational geometry
method for DTOA triangulation," in Proc, of 10th International
Conference on Information Fusion, 2007, pp. 1-7.
[12] W. H. Foy, "Position-Location Solutions by Taylor-Series Estimation,"
IEEE Transactions on Aerospace and Electronic Systems, vol. AES-12,
pp. 187-194, March 1976.
[13] D. J. Torrieri, "Statistical Theory of Passive Location Systems," IEEE
Transactions on Aerospace and Electronic Systems, vol. AES-20, no. 2,
pp. 183-198, March 1984.
[14] B. Friedlander, "A Passive Localization Algorithm and Its Accuracy
Analysis," IEEE Journal of Oceanic Engineering, vol. OE-12, no. 1, pp.
234-244, January 1987.
[15] H. C. Schau, and A. Z. Robinson, "Passive Source Localization
Employing Intersecting Spherical Surfaces from Time-of-Arrival
Differences," IEEE Transactions on Acoustics, Speech, and Signal
Processing, vol. ASSP-35, no. 8, pp. 1223-1225, August 1987.
[16] J. O. Smith, and J. S. Abel, "The Spherical Interpolation Method for
Source Localization," IEEE Journal of Oceanic Engineering, vol. OE-
12, no. 1, pp. 246-252, January 1987.
[17] J. S. Abel and J. O. Smith, "The Spherical Interpolation Method for
Closed-Form Passive Localization Using Range Difference
Measurements," in Proc. ICASSP-87, Dallas, TX, 1987, pp. 471-474.
[18] Y. T. Chan and K. C. Ho, "A Simple and Efficient Estimator for
Hyperbolic Location," IEEE Transactions on Signal Processing, vol. 42,
no. 8, pp. 1905-1915, August 1994.
@article{"International Journal of Electrical, Electronic and Communication Sciences:60795", author = "Muhammad R. Ahmed and Xu Huang and Dharmendra Sharma", title = "A Novel Framework for Abnormal Behaviour Identification and Detection for Wireless Sensor Networks", abstract = "Despite extensive study on wireless sensor network
security, defending internal attacks and finding abnormal behaviour
of the sensor are still difficult and unsolved task. The conventional
cryptographic technique does not give the robust security or detection
process to save the network from internal attacker that cause by
abnormal behavior. The insider attacker or abnormally behaved
sensor identificationand location detection framework using false
massage detection and Time difference of Arrival (TDoA) is
presented in this paper. It has been shown that the new framework
can efficiently identify and detect the insider attacker location so that
the attacker can be reprogrammed or subside from the network to
save from internal attack.", keywords = "Insider Attaker identification, Abnormal Behaviour,
Location detection, Time difference of Arrival (TDoA), Wireless
sensor network", volume = "6", number = "2", pages = "235-4", }
