Jack Sturgess, Sebastian Köhler, Simon Birnbach, Ivan Martinovic (University of Oxford)

Electric vehicle charging sessions can be authorised in different ways, ranging from smartphone applications to smart cards with unique identifiers that link the electric vehicle to the charging station. However, these methods do not provide strong authentication guarantees. In this paper, we propose a novel second factor authentication scheme to tackle this problem. We show that by using inertial sensor data collected from IMU sensors either embedded in the handle of the charging cable or on a separate smartwatch, users can be authenticated implicitly by behavioural biometrics as they unhook the cable from the charging station and plug it into their car at the start of a charging session. To validate the system, we conducted a user study (n=20) to collect data and we developed a suite of authentication models for which we achieve EERs of 0.06.

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PISE: Protocol Inference using Symbolic Execution and Automata Learning

Ron Marcovich, Orna Grumberg, Gabi Nakibly (Technion, Israel Institute of Technology)

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Preventing SIM Box Fraud Using Device Model Fingerprinting

BeomSeok Oh (KAIST), Junho Ahn (KAIST), Sangwook Bae (KAIST), Mincheol Son (KAIST), Yonghwa Lee (KAIST), Min Suk Kang (KAIST), Yongdae Kim (KAIST)

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A Robust Counting Sketch for Data Plane Intrusion Detection

Sian Kim (Ewha Womans University), Changhun Jung (Ewha Womans University), RhongHo Jang (Wayne State University), David Mohaisen (University of Central Florida), DaeHun Nyang (Ewha Womans University)

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