TB-ICT: A Trustworthy Blockchain-Enabled System for Indoor Contact Tracing in Epidemic Control

Recently, as a consequence of the coronavirus disease (COVID-19) pandemic, dependence on contact tracing (CT) models has significantly increased to prevent the spread of this highly contagious virus and be prepared for the potential future ones. Since the spreading probability of the novel coronavirus in indoor environments is much higher than that of the outdoors, there is an urgent and unmet quest to develop/design efficient, autonomous, trustworthy, and secure indoor CT solutions. Despite such an urgency, this field is still in its infancy. This article addresses this gap and proposes the trustworthy blockchain-enabled system for an indoor CT (TB-ICT) framework. The TB-ICT framework is proposed to protect privacy and integrity of the underlying CT data from unauthorized access. More specifically, it is a fully distributed and innovative blockchain platform exploiting the proposed dynamic Proof-of-Work (dPoW) credit-based consensus algorithm coupled with randomized hash window (W-Hash) and dynamic Proof-of-Credit (dPoC) mechanisms to differentiate between honest and dishonest nodes. The TB-ICT not only provides a decentralization in data replication but also quantifies the node’s behavior based on its underlying credit-based mechanism. For achieving a high localization performance, we capitalize on the availability of Internet of Things (IoT) indoor localization infrastructures, and develop a data-driven localization model based on bluetooth low-energy (BLE) sensor measurements. The simulation results show that the proposed TB-ICT prevents the COVID-19 from spreading by the implementation of a highly accurate CT model while improving the users’ privacy and security.

I. Introduction

Novel coronavirus disease (COVID-19) has abruptly and undoubtedly changed the world as we knew at the end of the 2nd decade of the 21st century. The highly contagious nature of the novel coronavirus has resulted in a global outbreak and has significantly imperiled global healthcare systems [1]. On account of such a highly contagious disease, people around the world are being asked to practice strict social distancing protocols. In this regard, contact tracing (CT) [2], [3], i.e., contact identification, contact listing, and follow-ups, becomes of paramount importance. Manual CT solutions [4] are labor intensive, making it inefficient, error prone, and time consuming in addition to suffering from potential security and privacy issues. For these reasons, the focus of recent research works [5] has been shifted toward the development of autonomous [6] models. Using technologies, such as the Internet of Things (IoT), mobile applications, and/or wearable devices, efficient autonomous CT solutions [4] can be implemented to immediately inform potential users at risk, while reducing the required amount of labor force. Since the spreading probability of COVID-19 in indoor environments is higher than that of outdoors [7], there is an urgent and unmet quest to develop/design trustworthy indoor CT solutions with highest achievable tracking capabilities. To achieve these objectives (i.e., trustworthiness and high indoor localization accuracy), we focus on: 1) Blockchain-enabled design, coupled with 2) Angle-of-Arrival (AoA)-based localization via bluetooth low-energy (BLE) beacons.