Seungho Kuk

A Feasibility Study and Development Framework Design for Realizing Smartphone-Based Vehicular Networking Systems

Designing and distributing effective vehicular safety applications can help significantly reduce the number of car accidents and assure the safety of many precious lives. However, despite the efforts from standardization bodies and industrial manufacturers, many studies suggest that it will take more than a decade for full deployment. We start this work with the hypothesis that smartphones may be suitable platforms for catalyzing the distribution of vehicular safety systems. Specifically, smartphones connected to their respective cellular networks can report sensing data to back-end application servers and exchange safety-related messages. This paper first evaluates the performance of the vehicular ad-hoc networking standards and the hardware platforms that implement them. Next, we perform empirical evaluations on the performance of cellular networks to confirm their applicability in vehicular networking. Based on our observations, we present the VoCell application development framework. VoCell, comprehends a set of components that eases the development of smartphone applications for vehicular networking applications. Using VoCell, developers can easily access internal and external sensing components and share this data to servers. We present a number of example applications developed using VoCell and evaluate their effectiveness in local and highway environments using a pilot deployment. We envision that VoCell can act as a building block for enabling new smartphone-based systems for vehicular networking applications.

Preventing Unfairness in the ETSI Distributed Congestion Control

The European Telecommunications Standards Institute (ETSI) framework imposes requirements on the exchange of periodic safety messages between components of intelligent transportation systems. First and foremost among these is the fair allocation of, and access to, wireless channels. The decentralized congestion control (DCC) algorithm has been standardized by ETSI to this end. However, DCC has a serious fairness problem, i.e, the beacon throughput can diverge by a factor of 100 or more, even among vehicles that are close together. In this letter, we demonstrate how the fairness problem manifests itself and propose a remedy so that DCC satisfies the fairness requirement.

Overcoming IoT Language Barriers Using Smartphone SDRs

In the Internet of Things (IoT) era, smartphones are expected to frequently interact with IoT devices and even facilitate various IoT applications. Due to limited roles, energy constraints, etc., however, IoT devices may use mission-tailored or proprietary wireless protocols that smartphones do not speak natively. In this paper, we propose a novel approach to the wireless “language barrier” problem between the smartphones and IoT devices of the future. We first demonstrate that smartphones have become powerful enough to process software defined radio (SDR) for some known wireless protocols. Moreover, we show that the SDRs can be packaged as “apps” and be downloaded from app stores for OS-independent deployment. Second, we show different SDR protocols on the smartphone can concurrently run through a shared RF to serve multi-tasked applications on it as might happen in diversified IoT environments. For proof-of-concept, we implement a prototype architecture that has all the SDR logic and supporting middleware on an Android smartphone which uses a USRP as the simple RF-end. Finally, we demonstrate that IEEE 802.11p and IEEE 802.15.4 SDRs on a smartphone, respectively, communicate with a ZigBee sensor mote, a ZigBee smart lightbulb, and a commercial Wireless Access in Vehicular Environment (WAVE) device, concurrently.

Empirical determination of efficient sensing frequencies for magnetometer-based continuous human contact monitoring

The high linear correlation between the smartphone magnetometer readings in close proximity can be exploited for physical human contact detection, which could be useful for such applications as infectious disease contact tracing or social behavior monitoring. Alternative approaches using other capabilities in smartphones have aspects that do not fit well with the human contact detection. Using Wi-Fi or cellular fingerprints have larger localization errors than close human contact distances. Bluetooth beacons could reveal the identity of the transmitter, threatening the privacy of the user. Also, using sensors such as GPS does not work for indoor contacts. However, the magnetometer correlation check works best in human contact distances that matter in infectious disease transmissions or social interactions. The omni-present geomagnetism makes it work both indoors and outdoors, and the measured magnetometer values do not easily reveal the identity and the location of the smartphone. One issue with the magnetometer-based contact detection, however, is the energy consumption. Since the contacts can take place anytime, the magnetometer sensing and recording should be running continuously. Therefore, how we address the energy requirement for the extended and continuous operation can decide the viability of the whole idea. However, then, we note that almost all existing magnetometer-based applications such as indoor location and navigation have used high sensing frequencies, ranging from 10 Hz to 200 Hz. At these frequencies, we measure that the time to complete battery drain in a typical smartphone is shortened by three to twelve hours. The heavy toll raises the question as to whether the magnetometer-based contact detection can avoid such high sensing rates while not losing the contact detection accuracy. In order to answer the question, we conduct a measurement-based study using independently produced magnetometer traces from three different countries. Specifically, we gradually remove high frequency components in the traces, while observing the correlation changes. As a result, we find that the human coexistence detection indeed tends to be no less, if not more, effective at the sampling frequency of 1 Hz or even less. This is because unlike the other applications that require centimeter-level precision, the human contacts detected anywhere within a couple of meters are valid for our purpose. With the typical smartphone battery capacity and at the 1 Hz sensing, the battery consumption is well below an hour, which is smaller by more than two hours compared with 10 Hz sampling and by almost eleven hours compared with 200 Hz sampling. With other tasks running simultaneously on smartphones, the energy saving aspect will only become more critical. Therefore, we conclude that sensing the ambient magnetic field at 1 Hz is sufficient for the human contact monitoring purpose. We expect that this finding will have a significant practicability implication in the smartphone magnetometer-based contact monitoring applications in general.

Poster: Towards Quick Angular Check to Rebuff Forged Position Attacks in Vehicular Communication

Although Wireless Access in Vehicular Environment (WAVE) will be legally enforced from 2020 after the recent move by the U.S. Government [1], there is still an unresolved security issue. It is data plausibility, which is not addressed in any standard that comprises the WAVE framework. In particular, an attacker may forge false position values in safety beacons in order to cause unsafe response from startled receiving vehicles. The data plausibility is a longstanding issue for which various approaches based on sensor fusion, behavior analysis and communication constraints have been proposed. However, none of these completely solve the problem.

Judging Dynamic Co-Existence with Smartphone Magnetometer Traces

Smartphone magnetometer traces can be used to check if the owners moved in proximity. Using time-lagged cross-correlation of the traces, a fine-resolution judgement can be made within a few meters in any formation. The technique works indoors and outdoors, with no communication infrastructure, with less power and higher resolution than GPS, and with less privacy violation than beaconing. Research and practice on human interactions, such as epidemiology and sociology that need fine contact tracing between complete strangers, can harness the technique.

Detecting False Position Attack in Vehicular Communications Using Angular Check

With Wireless Access in Vehicular Environment (WAVE) finalized for legal enforcement from 2020 after the recent move by the U.S. Government, data plausibility is still an unresolved security issue. In particular, an attacker may forge false position values in safety beacons in order to cause unsafe response from startled receiving vehicles. The data plausibility is a longstanding issue for which various approaches based on sensor fusion, behavior analysis and communication constraints have been proposed, but none of these completely solve the problem. This paper proposes an angle of arrival (AoA) based method to invalidate position forging adversaries such as roadside attackers. Built entirely on the WAVE framework, it can be used even when the traditional sensor fusion-based or behavior-based check is inapplicable. The proposed approach is a completely passive scheme that does not require more than an additional antenna that is strongly recommended for performance anyway.

Exploring Smartphones as WAVE Devices

In this paper, we explore the possibility of using smartphones as WAVE devices. When it is expected to take more than a decade from now to deploy the WAVE technology in full scale, smartphones running the WAVE protocol stack can bring the benefit of the technology earlier. In particular, we design and implement the lower layers of the WAVE stack in software defined radio (SDR) on smartphone platform and test its vehicle-to-vehicle (V2V) performance in the real driving scenarios. We also investigate the performance in the vehicle-to-pedestrian (V2P) communication context.