Abstract. Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called "A Line in the Sand" and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability on application performance. Our work includes multiple experimental deployments of over 90 sensors nodes at MacDill Air Force Base in Tampa, Florida, as well as other field experiments of comparable scale. Based on these experiences, we identify a set of key lessons and articulate a few of the challenges facing extreme scaling to tens or hundreds of thousands of sensor nodes.

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Geometric routing algorithms like GFG (GPSR) are lightweight, scalable algorithms that can be used to route in resource-constrained ad hoc wireless networks. However, such algorithms run on planar graphs only. To efficiently construct a planar graph, they require a unit-disk graph. To make the topology unit-disk, the maximum link length in the network has to be selected conservatively. In practical setting this leads to the designs where the node density is rather high. Moreover, the network diameter of a planar subgraph is greater than the original graph, which leads to longer routes. To remedy this problem, we propose a void traversal algorithm that works on arbitrary geometric graphs. We describe how to use this algorithm for geometric routing with guaranteed delivery and compare its performance with GFG.

The Sybil attack in unknown port networks such as wireless is not considered tractable. A wireless node is not capable of independently differentiating the universe of real nodes from the universe of arbitrary non-existent fictitious nodes created by the attacker. Similar to failure detectors, we propose to use universe detectors to help nodes determine which universe is real. In this paper, we (i) define several variants of the neighborhood discovery problem under Sybil attack (ii) propose a set of matching universe detectors (iii) demonstrate the necessity of additional topological constraints for the problems to be solvable: node density and communication range; (iv) present SAN D -an algorithm that solves these problems with the help of appropriate universe detectors, this solution demonstrates that the proposed universe detectors are the weakest detectors possible for each problem.