TY - GEN
T1 - Robust localization in wireless sensor networks through the revocation of malicious anchors
AU - Misra, Satyajayant
AU - Xue, Guoliang
AU - Shrivastava, Aviral
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - In a wireless sensor network (WSN), the sensor nodes (SNs) generally localize themselves with the help of anchors that are pre-deployed in the network. Time of Arrival (ToA) is a commonly used mechanism for SNs localization in WSNs. In ToA, the SNs localize themselves using the positions of the anchors and the time difference between the receipt of a radio and ultrasound signal transmitted by each anchor. In this setting, the localization process has a high risk of being subverted by malicious anchors that lie about their position and/or distance from the SNs. In this paper, we propose an efficient scheme that helps identify and revoke these malicious anchors. We use a mobile verifier (MV) that moves throughout the network, in some pre-determined manner, and obtains multiple location references from each anchor. For each anchor, the MV tests the mean and the variance of the collected sample to identify if the anchor is malicious. We show through simulations that our scheme successfully identifies more than 80% of malicious anchors with less than 60 references from each. Also, the percentage of false positives is close to 0.
AB - In a wireless sensor network (WSN), the sensor nodes (SNs) generally localize themselves with the help of anchors that are pre-deployed in the network. Time of Arrival (ToA) is a commonly used mechanism for SNs localization in WSNs. In ToA, the SNs localize themselves using the positions of the anchors and the time difference between the receipt of a radio and ultrasound signal transmitted by each anchor. In this setting, the localization process has a high risk of being subverted by malicious anchors that lie about their position and/or distance from the SNs. In this paper, we propose an efficient scheme that helps identify and revoke these malicious anchors. We use a mobile verifier (MV) that moves throughout the network, in some pre-determined manner, and obtains multiple location references from each anchor. For each anchor, the MV tests the mean and the variance of the collected sample to identify if the anchor is malicious. We show through simulations that our scheme successfully identifies more than 80% of malicious anchors with less than 60 references from each. Also, the percentage of false positives is close to 0.
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U2 - 10.1109/ICC.2007.508
DO - 10.1109/ICC.2007.508
M3 - Conference contribution
AN - SCOPUS:38549150969
SN - 1424403537
SN - 9781424403530
T3 - IEEE International Conference on Communications
SP - 3057
EP - 3062
BT - 2007 IEEE International Conference on Communications, ICC'07
T2 - 2007 IEEE International Conference on Communications, ICC'07
Y2 - 24 June 2007 through 28 June 2007
ER -