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PPCA is a lightweight, distributed, and privacy-preserving privacy-preserving collision avoidance scheme for autonomous UAVs. It integrates and turns privacy-preserving proximity testing solutions, traditionally adopted in online geo-social networks, into a real-time interactive approach to detect co-location among moving entities, and to avoid approaching collisions.

The details are provided in the paper, accepted and published by the prestigious IEEE Transactions on Dependable and Secure Computing.

The security properties of PPCA have been verified formally and experimentally by using the open-source tool ProVerif 2.01, demonstrating enhanced security protection with respect to state-of-the-art approaches.

In order to test the security properties, download the file ppca.pv and run: ./proverif ppca.pv | grep "RESULT". Further, in order to verify that the location is a strong secret (i.e. the attacker cannot launch offline guessing attacks on the location value), please follow the guidelines inside the code.

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

(^) Pietro Tedeschi (pietro dot tedeschi at tii dot ae)
(-) Savio Sciancalepore (s dot sciancalepore at tue dot nl)
(+) Roberto Di Pietro (rdipietro at hbku dot edu dot qa)

(^) Technology Innovation Institute, Secure Systems Research Center, Abu Dhabi, United Arab Emirates
(-) Security Group - Faculty of Mathematics and Computer Science, Eindhoven University of Technology (TU/e), Eindhoven, The Netherlands
(+) Division of Information and Computing Technology (ICT), College of Science and Engineering (CSE), Hamad Bin Khalifa University (HBKU), Doha, Qatar

PPCA is released under the GNU General Public License v3.0 license.