Another Look at Privacy-Preserving Automated Contact Tracing
- URL: http://arxiv.org/abs/2010.13462v1
- Date: Mon, 26 Oct 2020 09:59:15 GMT
- Title: Another Look at Privacy-Preserving Automated Contact Tracing
- Authors: Qiang Tang
- Abstract summary: A number of automated contact tracing solutions have been proposed and some have been deployed.
Security and privacy issues of these solutions are still open and under intensive debate.
We propose a venue-based ACT concept, which only monitors users' contacting history in virus-spreading-prone venues.
- Score: 3.0718680861621404
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In the current COVID-19 pandemic, manual contact tracing has been proven very
helpful to reach close contacts of infected users and slow down virus
spreading. To improve its scalability, a number of automated contact tracing
(ACT) solutions have proposed and some of them have been deployed. Despite the
dedicated efforts, security and privacy issues of these solutions are still
open and under intensive debate. In this paper, we examine the ACT concept from
a broader perspective, by focusing on not only security and privacy issues but
also functional issues such as interface, usability and coverage. We first
elaborate on these issues and particularly point out the inevitable privacy
leakages in existing BLE-based ACT solutions. Then, we propose a venue-based
ACT concept, which only monitors users' contacting history in
virus-spreading-prone venues and is able to incorporate different location
tracking technologies such as BLE and WIFI. Finally, we instantiate the
venue-based ACT concept and show that our instantiation can mitigate most of
the issues we have identified in our analysis.
Related papers
- Collaborative Inference over Wireless Channels with Feature Differential Privacy [57.68286389879283]
Collaborative inference among multiple wireless edge devices has the potential to significantly enhance Artificial Intelligence (AI) applications.
transmitting extracted features poses a significant privacy risk, as sensitive personal data can be exposed during the process.
We propose a novel privacy-preserving collaborative inference mechanism, wherein each edge device in the network secures the privacy of extracted features before transmitting them to a central server for inference.
arXiv Detail & Related papers (2024-10-25T18:11:02Z) - Provable Privacy Guarantee for Individual Identities and Locations in Large-Scale Contact Tracing [4.436902019991021]
Our paper proposes a highly scalable, practical contact tracing system called PREVENT.
It can work with a variety of location collection methods to gain a comprehensive overview of a person's trajectory.
Our system is very efficient and can provide real-time query services for large-scale datasets with millions of locations.
arXiv Detail & Related papers (2024-09-18T22:19:48Z) - 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) - CoAvoid: Secure, Privacy-Preserved Tracing of Contacts for Infectious
Diseases [25.014640577594566]
This paper proposes CoAvoid, a decentralized, privacy-preserved contact tracing system.
CoAvoid leverages the Google/Apple Exposure Notification (GAEN) API to achieve decent device compatibility and operating efficiency.
Compared with four state-of-art contact tracing applications, CoAvoid can reduce upload data by at least 90% and simultaneously resist wormhole and replay attacks.
arXiv Detail & Related papers (2022-01-20T12:19:21Z) - BU-Trace: A Permissionless Mobile System for Privacy-Preserving
Intelligent Contact Tracing [40.44797233933835]
coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented health crisis for the global.
Despite intensive research on digital contact tracing, existing solutions can hardly meet users' requirements on privacy and convenience.
We propose BU-Trace, a permissionless mobile system for privacy-preserving intelligent contact tracing based on QR code and NFC technologies.
arXiv Detail & Related papers (2021-01-24T06:11:09Z) - Differentially Private Multi-Agent Planning for Logistic-like Problems [70.3758644421664]
This paper proposes a novel strong privacy-preserving planning approach for logistic-like problems.
Two challenges are addressed: 1) simultaneously achieving strong privacy, completeness and efficiency, and 2) addressing communication constraints.
To the best of our knowledge, this paper is the first to apply differential privacy to the field of multi-agent planning.
arXiv Detail & Related papers (2020-08-16T03:43:09Z) - Epidemic Exposure Notification with Smartwatch: A Proximity-Based
Privacy-Preserving Approach [5.838266102141282]
Wireless technologies can play a key role in assisting contact tracing to quickly halt a local infection outbreak and prevent further spread.
We present a wearable proximity and exposure notification solution based on a smartwatch that also promotes safe physical distancing in business, hospitality, or recreational facilities.
arXiv Detail & Related papers (2020-07-08T19:55:33Z) - Trust and Transparency in Contact Tracing Applications [81.07729301514182]
The global outbreak of COVID-19 has led to efforts to manage and mitigate the continued spread of the disease.
One of these efforts include the use of contact tracing to identify people who are at-risk of developing the disease through exposure to an infected person.
There has been significant interest in the development and use of digital contact tracing solutions to supplement the work of human contact tracers.
The collection and use of sensitive personal details by these applications has led to a number of concerns by the stakeholder groups with a vested interest in these solutions.
arXiv Detail & Related papers (2020-06-19T20:29:24Z) - 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) - A Privacy-Preserving Solution for Proximity Tracing Avoiding Identifier
Exchanging [0.0]
We propose a solution leveraging GPS to detect proximity, and Bluetooth to improve accuracy, without enabling exchange of identifiers.
Unlike related existing solutions, no complex cryptographic mechanism is adopted, while ensuring that the server does not learn anything about locations of users.
arXiv Detail & Related papers (2020-05-20T18:48:20Z)
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.