TY - GEN
T1 - Attack detection in wireless localization
AU - Chen, Yingying
AU - Trappe, Wade
AU - Martin, Richard P.
PY - 2007
Y1 - 2007
N2 - Accurately positioning nodes in wireless and sensor networks is important because the location of sensors is a critical input to many higher-level networking tasks. However, the localization infrastructure can be subjected to non-cryptographic attacks, such as signal attenuation and amplification, that cannot be addressed by traditional security services. We propose several attack detection schemes for wireless localization systems. We first formulate a theoretical foundation for the attack detection problem using statistical significance testing. Next, we define test metrics for two broad localization approaches: multilateration and signal strength. We then derived both mathematical models and analytic solutions for attack detection for any system that utilizes those approaches. We also studied additional test statistics that are specific to a diverse set of algorithms. Our trace-driven experimental results provide strong evidence of the effectiveness of our attack detection schemes with high detection rates and low false positive rates across both an 802.11 (WiFi) network as well as an 802.15.4 (ZigBee) network in two real office buildings. Surprisingly, we found that of the several methods we describe, all provide qualitatively similar detection rates which indicate that the different localization systems all contain similar attack detection capability.
AB - Accurately positioning nodes in wireless and sensor networks is important because the location of sensors is a critical input to many higher-level networking tasks. However, the localization infrastructure can be subjected to non-cryptographic attacks, such as signal attenuation and amplification, that cannot be addressed by traditional security services. We propose several attack detection schemes for wireless localization systems. We first formulate a theoretical foundation for the attack detection problem using statistical significance testing. Next, we define test metrics for two broad localization approaches: multilateration and signal strength. We then derived both mathematical models and analytic solutions for attack detection for any system that utilizes those approaches. We also studied additional test statistics that are specific to a diverse set of algorithms. Our trace-driven experimental results provide strong evidence of the effectiveness of our attack detection schemes with high detection rates and low false positive rates across both an 802.11 (WiFi) network as well as an 802.15.4 (ZigBee) network in two real office buildings. Surprisingly, we found that of the several methods we describe, all provide qualitatively similar detection rates which indicate that the different localization systems all contain similar attack detection capability.
UR - http://www.scopus.com/inward/record.url?scp=34548359279&partnerID=8YFLogxK
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U2 - 10.1109/INFCOM.2007.228
DO - 10.1109/INFCOM.2007.228
M3 - Conference contribution
AN - SCOPUS:34548359279
SN - 1424410479
SN - 9781424410477
T3 - Proceedings - IEEE INFOCOM
SP - 1964
EP - 1972
BT - Proceedings - IEEE INFOCOM 2007
T2 - IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications
Y2 - 6 May 2007 through 12 May 2007
ER -