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MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
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ACM Transactions on Programming Languages and Systems (TOPLAS)
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
Energy-efficient surveillance system using wireless sensor networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
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SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
SeRLoc: Robust localization for wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
ROPE: robust position estimation in wireless sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
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SIROCCO'06 Proceedings of the 13th international conference on Structural Information and Communication Complexity
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IEEE Journal on Selected Areas in Communications
Universe Detectors for Sybil Defense in Ad Hoc Wireless Networks
SSS '08 Proceedings of the 10th International Symposium on Stabilization, Safety, and Security of Distributed Systems
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ESORICS'11 Proceedings of the 16th European conference on Research in computer security
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Position verification problem is an important building block for a large subset of wireless sensor networks (WSN) applications. As a result, the performance of the WSN degrades significantly when misbehaving nodes report false location information in order to fake their actual position. In this paper we propose the first deterministic distributed protocol for accurate identification of faking sensors in a WSN. Our scheme does notrely on a subset of trustednodes that cooperate and are not allowed to misbehave. Thus, any subset of nodes is allowed to try faking its position. As in previous approaches, our protocol is based on distance evaluation techniques developed for WSN.On the positive side, we show that when the received signal strength (RSS) technique is used, our protocol handles at most $\lfloor \frac{n}{2} \rfloor-2$ faking sensors. When the time of flight (ToF) technique is used, our protocol manages at most $\lfloor \frac{n}{2} \rfloor - 3$ misbehaving sensors. On the negative side, we prove that no deterministic protocol can identify faking sensors if their number is $\lceil \frac{n}{2}\rceil -1$. Thus, our scheme is almost optimal with respect to the number of faking sensors.We discuss application of our technique in the trusted sensor model. More specifically, our results can be used to minimize the number of trusted sensors that are needed to defeat faking ones.