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Privaros: A Framework for Privacy-Compliant Delivery Drones

Authors:

Rakesh Rajan Beck,

Abhishek Vijeev,

Vinod GanapathyAuthors Info & Claims

CCS '20: Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security

Pages 181 - 194

https://doi.org/10.1145/3372297.3417858

Published: 02 November 2020 Publication History

Abstract

We present Privaros, a framework to enforce privacy policies on drones. Privaros is designed for commercial delivery drones, such as the ones that will likely be used by Amazon Prime Air. Such drones visit various host airspaces, each of which may have different privacy requirements. Privaros uses mandatory access control to enforce the policies of these hosts on guest delivery drones. Privaros is tailored for ROS, a middleware popular in many drone platforms. This paper presents the design and implementation of Privaros's policy-enforcement mechanisms, describes how policies are specified, and shows that policy specification can be integrated with India's Digital Sky portal. Our evaluation shows that a drone running Privaros can robustly enforce various privacy policies specified by hosts, and that its core mechanisms only marginally increase communication latency and power consumption.

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Index Terms

Privaros: A Framework for Privacy-Compliant Delivery Drones
1. Security and privacy
  1. Systems security
    1. Operating systems security
      1. Mobile platform security

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CCS '20: Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security

October 2020

2180 pages

ISBN:9781450370899

DOI:10.1145/3372297

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Jay Ligatti
University of South Florida, USA
,
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University of South Florida, USA
,
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Jonathan Katz
University of Maryland, USA
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University of California-Santa Barbara, USA

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https://dl.acm.org/doi/10.1145/3664617
Wagner PBirnstill PBeyerer J(2024)DDS Security+: Enhancing the Data Distribution Service With TPM-based Remote AttestationProceedings of the 19th International Conference on Availability, Reliability and Security10.1145/3664476.3670442(1-11)Online publication date: 30-Jul-2024
https://dl.acm.org/doi/10.1145/3664476.3670442
Lu PZhang LLiu MSridhar KSokolsky OKong FLee I(2024)Recovery from Adversarial Attacks in Cyber-physical Systems: Shallow, Deep, and Exploratory WorksACM Computing Surveys10.1145/365397456:8(1-31)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3653974
Japp WLee VVagicherla SRubio-Medrano C(2024)Fly-ABAC: Attribute Based Access Control for the Navigation of Unmanned Aerial Vehicles2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825924(7471-7476)Online publication date: 15-Dec-2024
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Imam ZLacoste MArfaoui G(2021)Towards a Modular Attestation Framework for Flexible Data Protection for Drone Systems2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)10.1109/WiMob52687.2021.9606269(96-102)Online publication date: 11-Oct-2021
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Garikipati GRoshani Mathuria ASingh P(2020)HEDrone: Privacy-Preserving Proof-of-Alibi for Drone Compliance Based on Homomorphic EncryptionSecurity, Privacy, and Applied Cryptography Engineering10.1007/978-3-030-66626-2_8(147-166)Online publication date: 22-Dec-2020
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