Abstract
The proliferation of unmanned aerial Vehicles (UAVs) might be impeded because of rising concerns about citizen privacy in today’s society. Though some protocols and standards like no-fly-zones (NFZs) have been proposed for drone compliance, they expose the operational logistics of the drone in terms of its flight data. AliDrone is a recent protocol that verifies NFZ violations by proof-of-alibi (PoA) via sharing of drone’s trace with a trusted third party Auditor. The protocol leverages upon a trusted execution environment (TEE) to prevent malicious drone operators from forging geo-location information. In AliDrone, since the auditor learns the drone’s flight trace, the privacy of the drone is compromised. HEDrone addresses this issue of drone privacy: it uses homomorphic encryption to enable PoA over encrypted traces.
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References
Young, A.: Passenger jet carrying 240 people nearly hits a drone at 15,000ft, The Daily Mail, UK, 15 September 2018
British broadcasting corporation. Big rise in drone jail smuggling incidents, February 2016. http://www.bbc.com/news/uk-35641453
Javaid, A.Y., Sun, W., Devabhaktuni, V.K., Alam, M.: Cyber security threat analysis and modeling of an unmanned aerial vehicle system. In: 2012 IEEE Conference on Technologies for Homeland Security (HST), pp. 585–590. IEEE (2012)
Birnbach, S., Baker, R., Martinovic, I.: Wi-fly?: detecting privacy invasion attacks by consumer drones (2017)
Busset, J., et al.: Detection and tracking of drones using advanced acoustic cameras. In: Unmanned/Unattended Sensors and Sensor Networks XI; and Advanced Free-Space Optical Communication Techniques and Applications, vol. 9647, p. 96470F, International Society for Optics and Photonics (2015)
Nguyen, P., Truong, H., Ravindranathan, M., Nguyen, A., Han, R., Vu, T.: Matthan: drone presence detection by identifying physical signatures in the drone’s RF communication. In: Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services, pp. 211–224 (2017)
Rozantsev, A., Lepetit, V., Fua, P.: Flying objects detection from a single moving camera. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4128–4136 (2015)
Liu, T., Hojjati, A., Bates, A., Nahrstedt, K.: AliDrone: enabling trustworthy proof-of-alibi for commercial drone compliance. In: 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), pp. 841–852 (2018)
Brasser, F., Kim, D., Liebchen, C., Ganapathy, V., Iftode, L., Sadeghi, A.-R.: Regulating arm trustzone devices in restricted spaces. In: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2016, pp. 413–425, Association for Computing Machinery, New York (2016)
Javaid, A.Y., Sun, W., Devabhaktuni, V.K., Alam, M.: Cyber security threat analysis and modeling of an unmanned aerial vehicle system. In: 2012 IEEE Conference on Technologies for Homeland Security (HST), pp. 585–590 (2012)
Vijeev, A., Ganapathy, V., Bhattacharyya, C.: Regulating drones in restricted spaces. In: Proceedings of the 20th International Workshop on Mobile Computing Systems and Applications, HotMobile 2019, pp. 27–32, Association for Computing Machinery, New York (2019)
Beck, R.R., Vijeev, A., Ganapathy, V.: Privaros: a framework for privacy-compliant drones, arXiv preprint arXiv:2002.06512 (2020)
Blank, P., Kirrane, S., Spiekermann, S.: Privacy-aware restricted areas for unmanned aerial systems. IEEE Secur. Priv. 16(2), 70–79 (2018)
Dyer, J., Dyer, M., Xu, J.: Practical homomorphic encryption over the integers, arXiv preprint arXiv:1702.07588 (2017)
Peng, Y., Li, H., Cui, J., Zhang, J., Ma, J., Peng, C.: hope: improved order preserving encryption with the power to homomorphic operations of ciphertexts. Sci. China Inf. Sci. 60(062101), 2017 (2017)
Cheon, J.H., Kim, A., Kim, M., Song, Y.: Homomorphic encryption for arithmetic of approximate numbers. In: Takagi, T., Peyrin, T. (eds.) ASIACRYPT 2017. LNCS, vol. 10624, pp. 409–437. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70694-8_15
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Garikipati, G., Roshani, Mathuria, A., Singh, P. (2020). HEDrone: Privacy-Preserving Proof-of-Alibi for Drone Compliance Based on Homomorphic Encryption. In: Batina, L., Picek, S., Mondal, M. (eds) Security, Privacy, and Applied Cryptography Engineering. SPACE 2020. Lecture Notes in Computer Science(), vol 12586. Springer, Cham. https://doi.org/10.1007/978-3-030-66626-2_8
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