Wireless link signature: Measurements, methodologies, and applications

We study and advance unique representations of physical layer wireless links, and explore opportunities to use them in location distinction, secret key establishment, and perimeter distinction applications.;Location distinction is the ability to determine when a device has changed its position. We compare two existing location distinction methods, and then combine their benefits to develop a new method using a metric that we call complex temporal signature. We use a 2.4 GHz link measurement dataset to evaluate the three methods. We find that the complex temporal signature method performs significantly better than the existing methods. We also perform new measurements to understand and model the temporal behavior of our link signatures. We integrate our model in our location distinction mechanism and significantly reduce false alarms due to temporal variations of link signatures.;We propose an approach where wireless devices, interested in establishing a secret key, sample the link signature space in a physical area to collect and combine uncorrelated measurements to generate the key. We study the impact of mobility patterns in obtaining uncorrelated measurements and find that (i) when movement step size is larger than one foot, the measurements are mostly uncorrelated, and (ii) more diffusion in the mobility results in less correlation in the measurements. We develop efficient mechanisms to encode measurements and reconcile the differences in the bits extracted between the two devices. Our results show that our scheme generates very high entropy secret bits at a high rate.;Perimeter distinction is the ability to distinguish locations belonging to different perimeters. We examine the use of wireless received signal strength (RSS) and link signature, and propose multiple methods to retain good distinction rates even when the receiver faces power manipulation by malicious transmitters. Using extensive measurements of indoor and outdoor perimeters, we find that link signature outperforms RSS in various fading conditions in terms of accuracy. Even without using signal power, it can achieve accurate perimeter distinction of up to 80%. When we train our perimeter distinction method with multiple measurements within the same perimeter, we can improve the accuracy up to 98%.