Towards Large-Scale and Privacy-Preserving Contact Tracing in COVID-19 Pandemic: A Blockchain Perspective

Lv, Wenzhe; Wu, Sheng; Jiang, Chunxiao; Cui, Yuanhao; Qiu, Xuesong; Zhang, Yan

doi:10.1109/tnse.2020.3030925

Cited by 38 publications

(22 citation statements)

References 26 publications

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“…This is because this dependency keeps people healthy in terms of achieving social distancing requirements. Increasing dependency on mobile applications is tightly coupled with an increasing level of privacy threats [12]. Moreover, existing advanced methods that could be used to track users, such as those that gather private information [13,14], make privacy concerns more relevant.…”

Section: Motivation and Research Questionsmentioning

confidence: 99%

Preserving Location Privacy in the IoT against Advanced Attacks using Deep Learning

Alyousef¹,

Srinivasan²,

Alrahhal³

et al. 2022

IJACSA

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Location-based services (LBSs) have received a significant amount of recent attention from the research community due to their valuable benefits in various aspects of society. In addition, the dependency on LBS in the performance of daily tasks has increased dramatically, especially after the spread of the COVID-19 pandemic. LBS users use their real location to build LBS queries to take benefits. This makes location privacy vulnerable to attacks. The privacy issue is accentuated if the attacker is an LBS provider since all information about users is accessible. Moreover, the attacker can apply advanced attacks, such as map matching and semantic location attacks. In response to these issues, this work employs artificial intelligence to build a robust defense against advanced location privacy attacks. The key idea behind protecting the location privacy of LBS users is to generate smart dummy locations. Smart dummy locations are false locations with the same query probability as the real location, but they are far from both the real location and each other. Relying on the previous two conditions, the deep-learning-based intelligent finder ensures a high level of location privacy protection against advanced attacks. The attacker cannot recognize the dummies from the real location and cannot isolate the real location by a filtering process. In terms of entropy (the privacy protection metric), accuracy (the deep learning metric), and total execution time (the performance metric) and compared to the well-known DDA and BDA systems, the proposed system shows better results, where entropy = 15.9, accuracy = 9.9, and total execution time = 17 sec.

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Section: Motivation and Research Questionsmentioning

confidence: 99%

Preserving Location Privacy in the IoT against Advanced Attacks using Deep Learning

Alyousef¹,

Srinivasan²,

Alrahhal³

et al. 2022

IJACSA

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“…More recently, PoL has been proposed for contact tracing. In [51] , Bychain, a permissionless blokchain for location based tracing is presented. Witnesses may be WiFi Access Points, nodes equipped with BLE, or LTE base stations owned by an Internet Service Provider, all equipped with GPSs and identified by a couple of public-private keys.…”

Section: Blockchain For Contact Tracingmentioning

confidence: 99%

Blockchains for COVID-19 Contact Tracing and Vaccine Support: A Systematic Review

et al. 2021

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Several blockchain projects to help against COVID-19 are emerging at a fast pace, showing the potential of this disruptive technology to mitigate the multi-systemic threats the pandemic is posing on all phases of the emergency management and generate value for the economy and society as a whole. This survey investigates how blockchain technology can be useful in the scope of supporting health actions that can reduce the spread of COVID-19 infections and allow a return to normality. Since the prominent use of blockchains to mitigate COVID-19 consequences are in the area of contact tracing and vaccine/immunity passport support, the survey mainly focuses on these two classes of applications. The aim of the survey is to show that only a proper combination of blockchain technology with advanced cryptographic techniques can guarantee a secure and privacy preserving support to fight COVID-19. In particular, the paper first presents these techniques, i.e. zero-knowledge, Diffie Hellman, blind signatures, and proxy re-encryption, then describes how they are used in combination with blockchains to define robust and privacy-preserving solutions. Finally, a brief description of blockchain applications beyond contact tracing and vaccine certification is presented.

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“…Blockchain i Smart Contract, w tym przypadku, są realną alternatywą dla obaw o kwestie bezpieczeństwa i prywatności danych wszystkich stron działania systemu. Można wyróżnić w tym obszarze następujące przykłady [4][5][6].…”

Section: Stan Wiedzyunclassified

Implementation of the Digital COVID-19 Vaccination Passport based on Blockchain Protecting Privacy

Pukocz¹

2021

PAR

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The paper discusses proposals for implementing the COVID-19 digital Vaccination Passport based on Blockchain that protects privacy. Since the end of the last year, after the commencement of vaccination against COVID-19, there has been an intense discussion on the form of introducing such a tool and the consequences of its implementation. This discussion is taking place in many European countries. One element of this discussion was the safety and anonymity of the massively verified data of persons on vaccinations in various areas of society functioning. These issues are being resolved by the proposed digital Vaccination Passport system. This system uses two major methods: Blockchain and hash functions, which allow you to maintain security, privacy, and anonymity at the same time. To improve the intuitiveness and simplicity of the system operation, the QR code technology was proposed in the passport verification process. The system has been implemented and tested in the Amazon AWS cloud computing environment. A reference architecture based on Blockchain for the AWS environment was proposed, dedicated to large and demanding application solutions. In addition, the cloud environment offers access to many tools that were used in the system’s implementation, significantly increasing the security of the entire solution.

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Towards Large-Scale and Privacy-Preserving Contact Tracing in COVID-19 Pandemic: A Blockchain Perspective

Cited by 38 publications

References 26 publications

Preserving Location Privacy in the IoT against Advanced Attacks using Deep Learning

Preserving Location Privacy in the IoT against Advanced Attacks using Deep Learning

Blockchains for COVID-19 Contact Tracing and Vaccine Support: A Systematic Review

Implementation of the Digital COVID-19 Vaccination Passport based on Blockchain Protecting Privacy

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