Privadome: Protecting Citizen Privacy from Delivery Drones

@article{Pillai2022PrivadomePC,
  title={Privadome: Protecting Citizen Privacy from Delivery Drones},
  author={Gokulnath Pillai and Eikansh Gupta and Ajith Suresh and Vinod Ganapathy and Arpita Patra},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.04961}
}
As e-commerce companies begin to consider using delivery drones for customer fulfillment, there are growing concerns around citizen privacy. Drones are equipped with cameras, and the video feed from these cameras is often required as part of routine navigation, be it for semi-autonomous or fully-autonomous drones. Footage of ground-based citizens may be captured in this video feed, thereby leading to privacy concerns. This paper presents Privadome, a system that implements the vision of a… 

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References

SHOWING 1-10 OF 94 REFERENCES

Privaros: A Framework for Privacy-Compliant Delivery Drones

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.

AliDrone: Enabling Trustworthy Proof-of-Alibi for Commercial Drone Compliance

AliDrone is designed and implemented, a trustworthy PoA protocol that enables individual drones to prove their compliance with No-Fly-Zones to a third party Auditor, preventing malicious drone operators from being able to forge geo-location information.

Wi-Fly?: Detecting Privacy Invasion Attacks by Consumer Drones

This work uses a model of the attack structure to derive statistical metrics for movement and proximity, that are then applied to received communications between a drone and its controller and uses inexpensive commercial off-the-shelf hardware to detect drones that are carrying out privacy invasion attacks.

Spiders in the Sky: User Perceptions of Drones, Privacy, and Security

A laboratory study with 20 participants who interacted with a real or model drone to elicit user perceptions of privacy and security issues around drones is described and recommendations to improve drone design and regulations that enhance individual privacy andSecurity are made.

Flying Eyes and Hidden Controllers: A Qualitative Study of People’s Privacy Perceptions of Civilian Drones in The US

A novel and rich account of people’s privacy perceptions of drones for civilian uses both in general and under specific usage scenarios is provided, highlighting two heightened issues of drones: powerful yet inconspicuous data collection and hidden and inaccessible drone controllers.

Privacy in Urban Sensing with Instrumented Fleets, Using Air Pollution Monitoring As A Usecase

This paper builds a sample Android application that gives the least polluted route alternatives given a source-destination pair in a privacy preserved manner and provides privacy guarantees for the scenario mentioned above using Gaussian Process Regression based interpolation, Differential Privacy (DP), and Secure two-party computations.

Privacy Mechanisms for Drones: Perceptions of Drone Controllers and Bystanders

It was found that owner registration and automatic face blurring individually received most support from both controllers and bystanders, and respondents suggested using varied combinations of mechanisms under different drone usage scenarios, highlighting their context-dependent preferences.

I-Pic: A Platform for Privacy-Compliant Image Capture

I-Pic, a trusted software platform that integrates digital capture with user-defined privacy, shows that a practical, energy-efficient system that conforms to the privacy choices of many users within a scene can be built and deployed using current hardware.

PROTC: PROTeCting Drone's Peripherals through ARM TrustZone

This work proposes a new mechanism PROTC to protect the essential peripherals of the drone from being maliciously accessed through the feature of ARM TrustZone, and successfully shows that only authorized applications can access drone's protected peripherals.

Drones' Cryptanalysis - Smashing Cryptography with a Flicker

A new method that can detect whether a specific POI (point of interest) is being video streamed by a drone and an algorithm that differentiates FPV transmissions from other suspicious radio transmissions is presented.
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