Mahdi Akil (Karlstad University), Leonardo Martucci (Karlstad University), Jaap-Henk Hoepman (Radboud University)

In vehicular ad hoc networks (VANETs), vehicles exchange messages to improve traffic and passengers’ safety. In VANETs, (passive) adversaries can track vehicles (and their drivers) by analyzing the data exchanged in the network. The use of privacy-enhancing technologies can prevent vehicle tracking but solutions so far proposed either require an intermittent connection to a fixed infrastructure or allow vehicles to generate concurrent pseudonyms which could lead to identity-based (Sybil) attacks. In this paper, we propose an anonymous authentication scheme that does not require a connection to a fixed infrastructure during operation and is not vulnerable to Sybil attacks. Our scheme is built on attribute-based credentials and short lived pseudonyms. In it, vehicles interact with a central authority only once, for registering themselves, and then generate their own pseudonyms without interacting with other devices, or relying on a central authority or a trusted third party. The pseudonyms are periodically refreshed, following system wide epochs.

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Detection and Resolution of Control Decision Anomalies

Prof. Kang Shin (Kevin and Nancy O'Connor Professor of Computer Science, and the Founding Director of the Real-Time Computing Laboratory (RTCL) in the Electrical Engineering and Computer Science Department at the University of Michigan)

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Trellis: Robust and Scalable Metadata-private Anonymous Broadcast

Simon Langowski (Massachusetts Institute of Technology), Sacha Servan-Schreiber (Massachusetts Institute of Technology), Srinivas Devadas (Massachusetts Institute of Technology)

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Sometimes, You Aren’t What You Do: Mimicry Attacks against...

Akul Goyal (University of Illinois at Urbana-Champaign), Xueyuan Han (Wake Forest University), Gang Wang (University of Illinois at Urbana-Champaign), Adam Bates (University of Illinois at Urbana-Champaign)

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Breaking and Fixing Virtual Channels: Domino Attack and Donner

Lukas Aumayr (TU Wien), Pedro Moreno-Sanchez (IMDEA Software Institute), Aniket Kate (Purdue University / Supra), Matteo Maffei (Christian Doppler Laboratory Blockchain Technologies for the Internet of Things / TU Wien)

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