Mridula Singh (CISPA - Helmholtz Center for Information Security), Marc Roeschlin (ETH Zurich), Aanjhan Ranganathan (Northeastern University), Srdjan Capkun (ETH Zurich)

A number of safety- and security-critical applications such as asset tracking, smart ecosystems, autonomous vehicles and driver assistance functions, etc., are expected to benefit from the position information available through 5G.
Driven by the aim to support such a wide-array of location-aware services and applications, the current release of 5G seeks to explore ranging and positioning [1] as an integral part of 5G technology. In recent years, many attacks on positioning and ranging systems have been demonstrated, and hence it is important to build 5G systems that are resilient to distance and location manipulation attacks. No existing proposal either by 3GPP or the research community addresses the challenges of secure position estimation in 5G.
In this paper, we develop V-Range, the first secure ranging system that is fully compatible with 5G standards and can be implemented directly on top of existing 5G-NR transceivers.
We design V-Range, a system capable of executing secure ranging operations resilient to both distance enlargement and reduction attacks.

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MobFuzz: Adaptive Multi-objective Optimization in Gray-box Fuzzing

Gen Zhang (National University of Defense Technology), Pengfei Wang (National University of Defense Technology), Tai Yue (National University of Defense Technology), Xiangdong Kong (National University of Defense Technology), Shan Huang (National University of Defense Technology), Xu Zhou (National University of Defense Technology), Kai Lu (National University of Defense Technology)

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PoF: Proof-of-Following for Vehicle Platoons

Ziqi Xu (University of Arizona), Jingcheng Li (University of Arizona), Yanjun Pan (University of Arizona), Loukas Lazos (University of Arizona, Tucson), Ming Li (University of Arizona, Tucson), Nirnimesh Ghose (University of Nebraska–Lincoln)

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Reflections on Artifact Evaluation

Dr. Eric Eide (University of Utah)

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ProvTalk: Towards Interpretable Multi-level Provenance Analysis in Networking Functions...

Azadeh Tabiban (CIISE, Concordia University, Montreal, QC, Canada), Heyang Zhao (CIISE, Concordia University, Montreal, QC, Canada), Yosr Jarraya (Ericsson Security Research, Ericsson Canada, Montreal, QC, Canada), Makan Pourzandi (Ericsson Security Research, Ericsson Canada, Montreal, QC, Canada), Mengyuan Zhang (Department of Computing, The Hong Kong Polytechnic University, China), Lingyu Wang (CIISE, Concordia University, Montreal, QC, Canada)

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