Andreas Unterweger, Fabian Knirsch, Clemens Brunner and Dominik Engel (Center for Secure Energy Informatics, Salzburg University of Applied Sciences, Puch bei Hallein, Austria)

The increasing amount of electric vehicles and a growing electric vehicle ecosystem is becoming a highly heterogeneous environment with a large number of participants that interact and communicate. Finding a charging station, performing vehicle-to-vehicle charging or processing payments poses privacy threats to customers as their location and habits can be traced. In this paper, we present a privacy-preserving solution for grid-to-vehicle charging, vehicle-to-grid charging and vehicle to-vehicle charging, that allows for finding the right charging option in a competitive market environment and that allows for built-in payments with adjustable and limited risk for both, producers and consumers of electricity. The proposed approach builds on blockchain technology and extends a state-of-the-art protocol with payments, while still preserving the privacy of the users. The protocol is evaluated with respect to privacy, risk and scalability. It is shown that pseudonymity and location privacy (against third parties) is guaranteed throughout the protocol, even beyond a single protocol session. In addition, both, risk and scalability can be adjusted based on the used blockchain.

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Short Paper: Declarative Demand-Driven Reverse Engineering

Yihao Sun, Jeffrey Ching, Kristopher Micinski (Department of Electical Engineering and Computer Science, Syracuse University)

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PHOENIX: Device-Centric Cellular Network Protocol Monitoring using Runtime Verification

Mitziu Echeverria (The University of Iowa), Zeeshan Ahmed (The University of Iowa), Bincheng Wang (The University of Iowa), M. Fareed Arif (The University of Iowa), Syed Rafiul Hussain (Pennsylvania State University), Omar Chowdhury (The University of Iowa)

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PASS: A System-Driven Evaluation Platform for Autonomous Driving Safety...

Zhisheng Hu (Baidu Security), Junjie Shen (UC Irvine), Shengjian Guo (Baidu Security), Xinyang Zhang (Baidu Security), Zhenyu Zhong (Baidu Security), Qi Alfred Chen (UC Irvine) and Kang Li (Baidu Security)

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