ABSTRACT
During the COVID-19 pandemic, it was necessary to validate a person's health status along with their identity to permit travel. This was facilitated via paper-based certificates and centralized digital apps. Even after COVID-19, it is anticipated that such health status verifications will be required for travel and other purposes. As a result, there needs to be an additional credential, a "Health Passport," that establishes whether a person satisfies the health requirements for various purposes. Digital credentials so prepared should be trustable, unforgeable, and verifiable. The Health Passport should be designed to protect the end-users' privacy and give people control over the data they use to confirm their credentials. This article explores the requirements for a generalized Health Passport system and uses agent-oriented modeling (AOM) to design a blockchain-based self-sovereign identity (SSI) system integrated with the Personal Health Record (PHR) to address this requirement. The article demonstrates the feasibility of the solution by implementing a proof of concept on Hyperledger Indy and Aries, integrated with the PHR - MediTrans. Credential issuance and verification time were calculated, and it was observed that the time overhead was minimal. This solution allows users to verify their credentials with the verifier without revealing any significant personal information. Our solution can be integrated into any PHR solution as the SSI solution is added as a plugin to the PHR accessible via a mobile/web app.
ABSTRACT
The COVID-19 pandemic has severely affected daily life and caused a great loss to the global economy. Due to the very urgent need for identifying close contacts of confirmed patients in the current situation, the development of automated contact tracing app for smart devices has attracted more attention all over the world. Compared with expensive manual tracing approach, automated contact tracing apps can offer fast and precise tracing service, however, over-pursing high efficiency would lead to the privacy-leaking issue for app users. By combing with the benign properties (e.g., anonymity, decentralization, and traceability) of blockchain, we propose an efficient privacy-preserving solution in automated tracing scenario. Our main technique is a combination of non-interactive zero-knowledge proof and multi-signature with public key aggregation. By means of aggregating multiple signatures from different contacts at the mutual commitment phase, we only need fewer zero-knowledge proofs to complete the task of identifying contacts. It inherently leads to the benefits of saving storage and consuming less time for running verification algorithm on blockchain. Furthermore, we perform an experimental comparison by timing the execution of signature verification with and without aggregate signature, respectively. It shows that our solution can actually preserve the full-fledged privacy protection property with a lower computational cost. © 2022
ABSTRACT
Advancements in mobile computing and embedded system technologies show superiority in controlling the transmission of a virus during the COVID-19 pandemic. They provide rapid contact data compared to manual contact tracing and medical monitoring methodologies. Data tracing capabilities were achieved by existing technologies via the utilization of smartphone-based exposure notifications systems and proximity sensing tools based on Bluetooth/GPS. Such systems lack user privacy and data anonymization capabilities, it also requires that users have continuous access to smartphones. This paper proposes the development of a lightweight wearable prototype for contact tracing. The proposed system is based on the deployment of an IoT development board, incorporated with a Bluetooth chipset for proximity sensing. To overcome the problem of user-to-smartphone accessibility, the processing of contact data by the exposure notification system has been migrated from mobile computing to a contact tracer management server that is managed by the community. Daily contact exposures to the virus are recorded by each user's contact tracing system and stored in the user's blockchain. Data integrity and immunity against data injection attacks were achieved via the implementation of lightweight block chaining and validation schemes. Data anonymization was also supported via the utilization of the onboard AES crypto engine. Meanwhile, support for user anonymity was incorporated into the proposed system through the implementation of an anonymous authentication protocol based on the Zero-Knowledge Proof (ZKP) approach. Finally, we have analyzed the performance of the system in terms of power consumption under various systems settings, such as encryption key size and the required number of ZKP validation attempts per authentication session.
ABSTRACT
To control coronavirus disease 2019 (COVID-19), most countries have opted for a containment policy. When a decision of decontainment has to be taken, a question emerges regarding the digital strategy to adopt: Should we track citizens? All of them or only persons who contracted COVID-19? Should we take measures to protect elderly people or people suffering from co-morbidities? Many applications and approaches have been proposed to ensure public safety in the context of COVID-19. In this chapter, we will start by making an inventory of these applications, discuss strategies and technologies adopted, and categorize them. Thereafter we will present an approach consisting in calculating a vulnerability score to propose a solution for protecting people at risk. Then, we will detail the architecture of “uTakeCare, " an open-source application that we have implemented, as well as the method used to calculate the vulnerability score. This method is based on a belief function theory and machine learning techniques. Finally, we will discuss the ethical and legal issues of this application and the methods to be used to address them (e.g., zero-knowledge proof, smart contracts, etc.) as a way to complement general data protection regulation (roadmap to develop personal data) requirements with ethics-by-design and self-sovereign identity solutions. © 2021 Elsevier Inc. All rights reserved.
ABSTRACT
Counterfeiting drugs has been a global concern for years. Considering the lack of transparency within the current pharmaceutical distribution system, research has shown that blockchain technology is a promising solution for an improved supply chain system. This study aims to explore the current solution proposals for distribution systems using blockchain technology. Based on a literature review on currently proposed solutions, it is identified that the secrecy of the data within the system and nodes' reputation in decision making has not been considered. The proposed prototype uses a zero-knowledge proof protocol to ensure the integrity of the distributed data. It uses the Markov model to track each node's 'reputation score' based on their interactions to predict the reliability of the nodes in consensus decision making. Analysis of the prototype demonstrates a reliable method in decision making, which concludes with overall improvements in the system's confidentiality, integrity, and availability. The result indicates that the decision protocol must be significantly considered in a reliable distribution system. It is recommended that the pharmaceutical distribution systems adopt a relevant protocol to design their blockchain solution. Continuous research is required further to increase performance and reliability within blockchain distribution systems.
Subject(s)
Blockchain , Confidentiality , Pharmaceutical Preparations , Reproducibility of Results , TechnologyABSTRACT
The COVID-19 pandemic has severely affected daily life and caused a great loss to the global economy. Due to the very urgent need for identifying close contacts of confirmed patients in the current situation, the development of automated contact tracing app for smart devices has attracted more attention all over the world. Compared with expensive manual tracing approach, automated contact tracing apps can offer fast and precise tracing service, however, over-pursing high efficiency would lead to the privacy-leaking issue for app users. By combing with the benign properties (e.g., anonymity, decentralization, and traceability) of blockchain, we propose an efficient privacy-preserving solution in automated tracing scenario. Our main technique is a combination of non-interactive zero-knowledge proof and multi-signature with public key aggregation. By means of aggregating multiple signatures from different contacts at the mutual commitment phase, we only need fewer zero-knowledge proofs to complete the task of identifying contacts. It inherently leads to the benefits of saving storage and consuming less time for running verification algorithm on blockchain. Furthermore, we perform an experimental comparison by timing the execution of signature verification with and without aggregate signature, respectively. It shows that our solution can actually preserve the full-fledged privacy protection property with a lower computational cost.
ABSTRACT
Driven by the increased consciousness in data ownership and privacy, zero-knowledge proofs (ZKPs) have become a popular tool to convince a third party of the truthfulness of a statement without disclosing any further information. As ZKPs are rather complex to design, frameworks that transform high-level languages into ZKPs have been proposed. We propose Circuitree, a Datalog reasoner in zero-knowledge. Datalog is a high-level declarative logic language that is generally used for querying. Furthermore, as a logic language, it can also be used to solve logic problems. An application using Circuitree can efficiently generate ZKPs, based on Datalog rules and encrypted data, to prove that a certain conclusion follows from a Datalog ruleset and encrypted input data. Compared to existing frameworks, which generally use their own limited imperative languages, Circuitree uses an existing high-level declarative language. We point out several applications for Circuitree, including EU Digital COVID Certificates and privacy-preserving access control for peer-to-peer (p2p) networks. Circuitree’s performance is evaluated for access control in a p2p network. First results show that our approach allows for fast proofs and proof verification for this application. Author
ABSTRACT
People face numerous severe problems in their everyday life. Extortion, corruption, threat, harassment, negligence, poor public service, etc., are some common problems people are dealing with everyday. As it may take a long time, most of the victims do not have the intention to complain anymore. As a result, these issues are getting worse rather than getting resolved. There are some ways online to contact and complain to the competent authorities. However, a complainant may be hesitant to complain in fear of insecurity because of the transparency issue of a centralized system. To resolve the issues, in this paper, we will present a blockchain-based anonymous, transparent, and decentralized platform, where people can complain anonymously and interact with the authorities to resolve their complaints. An authority can start resolving a complaint after receiving it from the platform. Those facing a similar problem or evaluating a problem to be prioritized can support/oppose the complaint. Complaints like damaged roads or pandemic situations like Covid-19 may need some financial support to be solved. In this case, authorities can start crowdfunding where both complainants and authorities can donate. Ultimately, we can claim that our proposed blockchain-based platform will be one of the most secure and reliable platforms for complainants to complain about their issues. © 2021 IEEE.