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Abstract
Obtaining accurate positions of nodes in wireless and sensor networks is important because the location of sensors is a critical input to many high-level services. Such services include location-aware content delivery, health-care monitoring, emergency rescue and recovery, and location-based access control. However, the localization infrastructure can be subjected to non-cryptographic attacks which cannot be addressed by traditional security services. In this talk, I will first describe a representative set of localization mechanisms and algorithms. Then, I will present our study on the robustness of these algorithms to signal strength attacks. Localization utilizing received signal strength measurement is an attractive approach because it can re-use the existing wireless infrastructure, presenting a tremendous cost savings over deploying localization-specific hardware. Further, I will propose several attack detection schemes for wireless localization systems. We formulate a theoretical foundation for the attack detection problem using statistical significance testing. Our experimental results provide strong evidence of the effectiveness of our approaches 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.
Yingying (Jennifer) Chen is a Ph.D. candidate in the Computer Science Department at Rutgers University. Her research interests span security in networks, systems and software, as well as wireless and sensor networks. She is interested in using statistical methods and machine learning techniques to classify and model network and system problems. She is a member of Wireless Information Network Laboratory (WINLAB) at Rutgers University. Concurrent to her studies, Yingying is employed at Bell Laboratories (Lucent Technologies) as a system architect and project lead. She is involved in managing and developing numerous projects at Bell Labs, ranging from optical networking systems to integrating voice/data services with ATM switches.
This seminar is sponsored by iNetS.
For more information please contact: Prof. Manu Malek, (201) 216-5611.
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