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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Evan Allen (Virginia Tech), Zeb Bowden (Virginia Tech Transportation Institute), Randy Marchany (Virginia Tech), J. Scot Ransbottom (Virginia Tech)

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OBI: a multi-path oblivious RAM for forward-and-backward-secure searchable encryption

Zhiqiang Wu (Changsha University of Science and Technology), Rui Li (Dongguan University of Technology)

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PPA: Preference Profiling Attack Against Federated Learning

Chunyi Zhou (Nanjing University of Science and Technology), Yansong Gao (Nanjing University of Science and Technology), Anmin Fu (Nanjing University of Science and Technology), Kai Chen (Chinese Academy of Science), Zhiyang Dai (Nanjing University of Science and Technology), Zhi Zhang (CSIRO's Data61), Minhui Xue (CSIRO's Data61), Yuqing Zhang (University of Chinese Academy of Science)

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Securing Lidar Communication through Watermark-based Tampering Detection (Long)

Michele Marazzi, Stefano Longari, Michele Carminati, Stefano Zanero (Politecnico di Milano)

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