A crucial concern for any network is security, and how to design sensor networks to detect and defend against intrusion — in other words, where to put sensors to ensure they detect intrusion. Researchers in this area have created applications specific to the design of sensor networks to detect security threats and provide support for security decisions in situations of uncertainty and time pressure, and have created decision-analysis detection mechanisms using stochastic modeling. This work has also extended to the natural world, with researchers using environmental sensors and ocean models to predict current flow in estuaries, to determine the best place to place sensors.
Professor Jeffrey Nickerson, along with fellow researcher Toshihiko Matsuka, of Japan, has received a patent related to work aiming to detect hostile intent from movement patterns.
Ben-Zvi, T. and Nickerson, J. V. "Intruder Detection: An Optimal Decision Analysis Strategy." IEEE Transactions on Systems, Man and Cybernetics: Part C, in press.
Ben-Zvi T. and Nickerson, J.V. "Decision Analysis: Environmental Learning Automata for Sensor Placement." IEEE Sensors, in press.
Kruger, D., Shi, H., Samaan, M., Nickerson, J.V. and Imas, L. "Dynamic UUV Path Planning in an Estuarine Current Field." Journal of Underwater Acoustics, JUA(USN) 59, 449-464 (2009).
Kruger, D., Shi, H., Samaan, M., Chesley, D., Nickerson, J.V. and Imas, L. "A New Technique for Efficient Localization: The Multiple Analytical Distribution Filter (MADF)." Journal of Underwater Acoustics, JUA (USN) 59, 465-481 (2009).
Kruger, D., Shi, H., Chen, Y., Liu, H., Yang, J. and Imas, L. "Using a Multiple Analytical Distribution Filter for Underwater Localization." Proceedings of the SPIE Europe Security Defense, 2009.
Olariu, S., and Nickerson, J.V. "A Probabilistic Approach to Integration." Decision Support Systems (45: 4), pp. 746-763, November 2008.