Decentralized is not risk-free: Understanding public perceptions of
privacy-utility trade-offs in COVID-19 contact-tracing apps
- URL: http://arxiv.org/abs/2005.11957v1
- Date: Mon, 25 May 2020 07:50:51 GMT
- Title: Decentralized is not risk-free: Understanding public perceptions of
privacy-utility trade-offs in COVID-19 contact-tracing apps
- Authors: Tianshi Li, Jackie (Junrui) Yang, Cori Faklaris, Jennifer King, Yuvraj
Agarwal, Laura Dabbish, Jason I. Hong
- Abstract summary: We present a survey study that examined people's willingness to install six different contact-tracing apps.
We found that the majority of people in our sample preferred to install apps that use a centralized server for contact tracing.
We also found that the majority of our sample preferred to install apps that share diagnosed users' recent locations in public places to show hotspots of infection.
- Score: 13.240901989243104
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Contact-tracing apps have potential benefits in helping health authorities to
act swiftly to halt the spread of COVID-19. However, their effectiveness is
heavily dependent on their installation rate, which may be influenced by
people's perceptions of the utility of these apps and any potential privacy
risks due to the collection and releasing of sensitive user data (e.g., user
identity and location). In this paper, we present a survey study that examined
people's willingness to install six different contact-tracing apps after
informing them of the risks and benefits of each design option (with a
U.S.-only sample on Amazon Mechanical Turk, $N=208$). The six app designs
covered two major design dimensions (centralized vs decentralized, basic
contact tracing vs. also providing hotspot information), grounded in our
analysis of existing contact-tracing app proposals.
Contrary to assumptions of some prior work, we found that the majority of
people in our sample preferred to install apps that use a centralized server
for contact tracing, as they are more willing to allow a centralized authority
to access the identity of app users rather than allowing tech-savvy users to
infer the identity of diagnosed users. We also found that the majority of our
sample preferred to install apps that share diagnosed users' recent locations
in public places to show hotspots of infection. Our results suggest that apps
using a centralized architecture with strong security protection to do basic
contact tracing and providing users with other useful information such as
hotspots of infection in public places may achieve a high adoption rate in the
U.S.
Related papers
- Protect Your Score: Contact Tracing With Differential Privacy Guarantees [68.53998103087508]
We argue that privacy concerns currently hold deployment back.
We propose a contact tracing algorithm with differential privacy guarantees against this attack.
Especially for realistic test scenarios, we achieve a two to ten-fold reduction in the infection rate of the virus.
arXiv Detail & Related papers (2023-12-18T11:16:33Z) - How mass surveillance can crowd out installations of COVID-19 contact
tracing apps [6.015556590955814]
During the COVID-19 pandemic, many countries have developed and deployed contact tracing technologies to curb the spread of the disease.
This paper analyzes situations where centralized mass surveillance technologies are deployed simultaneously with a voluntary contact tracing mobile app.
arXiv Detail & Related papers (2021-10-04T17:07:47Z) - What Makes People Install a COVID-19 Contact-Tracing App? Understanding
the Influence of App Design and Individual Difference on Contact-Tracing App
Adoption Intention [15.031178068213508]
Smartphone-based contact-tracing apps are a promising solution to help scale up the conventional contact-tracing process.
We present a national-scale survey experiment in the U.S. to investigate the effects of app design choices and individual differences on COVID-19 contact-tracing app adoption intentions.
arXiv Detail & Related papers (2020-12-22T23:46:47Z) - Towards Mass Adoption of Contact Tracing Apps -- Learning from Users'
Preferences to Improve App Design [3.187723878624947]
We explore user preferences for contact tracing apps using market research techniques and conjoint analysis.
Our results confirm the privacy-preserving design of most European contact tracing apps.
We conclude that adding goal-congruent features will play an important role in fostering mass adoption.
arXiv Detail & Related papers (2020-11-24T19:08:09Z) - Emerging App Issue Identification via Online Joint Sentiment-Topic
Tracing [66.57888248681303]
We propose a novel emerging issue detection approach named MERIT.
Based on the AOBST model, we infer the topics negatively reflected in user reviews for one app version.
Experiments on popular apps from Google Play and Apple's App Store demonstrate the effectiveness of MERIT.
arXiv Detail & Related papers (2020-08-23T06:34:05Z) - Mind the GAP: Security & Privacy Risks of Contact Tracing Apps [75.7995398006171]
Google and Apple have jointly provided an API for exposure notification in order to implement decentralized contract tracing apps using Bluetooth Low Energy.
We demonstrate that in real-world scenarios the GAP design is vulnerable to (i) profiling and possibly de-anonymizing persons, and (ii) relay-based wormhole attacks that basically can generate fake contacts.
arXiv Detail & Related papers (2020-06-10T16:05:05Z) - Decentralized Privacy-Preserving Proximity Tracing [50.27258414960402]
DP3T provides a technological foundation to help slow the spread of SARS-CoV-2.
System aims to minimise privacy and security risks for individuals and communities.
arXiv Detail & Related papers (2020-05-25T12:32:02Z) - COVI White Paper [67.04578448931741]
Contact tracing is an essential tool to change the course of the Covid-19 pandemic.
We present an overview of the rationale, design, ethical considerations and privacy strategy of COVI,' a Covid-19 public peer-to-peer contact tracing and risk awareness mobile application developed in Canada.
arXiv Detail & Related papers (2020-05-18T07:40:49Z) - How good is good enough for COVID19 apps? The influence of benefits,
accuracy, and privacy on willingness to adopt [24.202334512830255]
A growing number of contact tracing apps are being developed to complement manual contact tracing.
We evaluate the effect of both accuracy and privacy concerns on reported willingness to install COVID19 contact tracing apps.
arXiv Detail & Related papers (2020-05-09T01:53:52Z) - ACDC-Tracing: Towards Anonymous Citizen-Driven Contact Tracing [0.0]
ACDC-Tracing is an anonymous, voucher-based contact tracing solution.
People who test positive are given an anonymous voucher which they can share with a limited number of people whom they think they might be infected.
This is a fully anonymous solution which does not require any sharing of location data, Bluetooth, or having an app installed on people's mobile device.
arXiv Detail & Related papers (2020-04-16T05:16:08Z) - Give more data, awareness and control to individual citizens, and they
will help COVID-19 containment [74.10257867142049]
Contact-tracing apps are being proposed for large scale adoption by many countries.
A centralized approach raises concerns about citizens' privacy and needlessly strong digital surveillance.
We advocate a decentralized approach, where both contact and location data are collected exclusively in individual citizens' "personal data stores"
arXiv Detail & Related papers (2020-04-10T20:30:37Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.