Enabling Secure and Spontaneous Communication between Mobile Devices using Common Radio Environment

With the proliferation of mobile devices, spontaneous interactions between co-located devices that do not know each other a priori will become commonplace. Securing these interactions against eavesdropping and man-in-themiddle attacks is an important and challenging task. In this paper, we postulate that mobile devices that are positioned in close proximity may be able to derive a shared secret to secure their communication by monitoring fluctuations in the signal strength of existing ambient radio sources (GSM cell towers or WiFi access points) in their common environment. We explore the feasibility of deriving locationbased secrets and describe two approaches for how such a secret could be used to secure spontaneous communication. Deriving location-based secrets is a hard problem because while the radio environment perceived by various devices in close proximity is similar, it is not identical.

Algorithms for Detecting Motion of a GSM Mobile Phone

In this paper we detail two algorithms for detecting that a GSM mobile phone is moving (or stationary, since this is when the phone is simply not moving). These algorithms, in early experiments, show excellent promise and require nothing from the mobile phone other than radio signals that the phone must have to perform its normal function. We also discuss our approach to determine not only if a phone is mobile but also to differentiate motion based on walking from motion caused by traveling by car

Cross-Layer Flow Control in Lightly-Loaded Multi-Hop Ad Hoc Networks

The throughput in multi-hop ad hoc networks (MANETs) is highly dependent on the sending rate and the route length from the source node to the destination. Sending packets at the optimal rate for a given route length maximizes throughput in the network, whereas slightly increasing the sending rate over the optimal value may decrease throughput by up to 55%

Tracking Vehicular Speed Variations by Warping Mobile Phone Signal Strengths

Abstract—In this paper, we consider the problem of tracking fine-grained speeds variations of vehicles using signal strength traces from GSM enabled phones. Existing speed estimation techniques using mobile phone signals can provide longer-term speed averages but cannot track short-term speed variations. Understanding short-term speed variations, however, is important in a variety of traffic engineering applications—for example, it may help distinguish slow speeds due to traffic lights from traffic congestion when collecting real time traffic information. Usingmobilephonesinsuchapplicationsisparticularlyattractive because it can be readily obtained from a large number of vehicles. Our approach is founded on the observation that the largescale path loss and shadow fading components of signal strength readings (signal profile) obtained from the mobile phone on any given road segment appear similar over multiple trips along the same road segment except for distortions along the time axis due to speed variations. We therefore propose a speed tracking techniquethatusesaDerivative DynamicTimeWarping(DDTW) algorithm to realign a given signal profile with a known training profile from the same road. The speed tracking technique then translates the warping path (i.e., the degree of stretching and compressing needed for alignment) into an estimated speed trace. Using 6.4 hours of GSM signal strength traces collected from a vehicle, we show that our algorithm can estimate vehicular speed with a median error of ± 5mph compared to using a GPS and can capture significant speed variations on road segments with a precision of 68 % and a recall of 84%. I

Are GSM Phones THE Solution for Localization

In this paper, we argue that localization solution based on cellular phone technology, specifically GSM phones, is a sufficient and attractive option in terms of coverage and accuracy for a wide range of indoor, outdoor, and placebased location-aware applications. We present preliminary results that indicate that GSM-based localization systems have the potential to detect the places that people visit in their everyday lives, and can achieve median localization accuracies of 5 and 75 meters for indoor and outdoor environments, respectively.