Privacy Preservation of User Identity in Contact Tracing for COVID-19-Like Pandemics Using Edge Computing

Abstract

Pandemic and infectious disease outbreaks put pressure on health authorities and require lockdowns. These outbreaks, which strain limited healthcare resources, must be swiftly controlled and monitored. A large number of healthcare authorities are currently investigating automated systems to support outbreak monitoring and control. However, current contact tracing systems face many privacy, participation, and power constraints. Furthermore, elderly or less financially able individuals often cannot participate in automated contact tracing due to not owning a smartphone. This paper proposes a new system that enables health authorities to track exposure among individuals participating in the automated system, aid health authorities in interviewing non-participating individuals, and minimize the processing required by offloading to nearby edge computing devices. The proposed system utilizes edge servers to assist health authorities in tracking users who withdraw from or are unable to use contact tracing. Edge computing devices have access to more contextual information, resulting in minimal data collection and thus enabling businesses, houses, and offices to participate in contact tracing as locations. Edge computing devices enable location-based data collection of contact tracing data using proximity-based sensors for offices, homes, and shops, thereby assisting health authorities to notify users of exposure without disclosing the identities of businesses or individuals. Moreover, the proposed system reduces the overall power for end users up to 97% by delegating contact tracing to nearby edge computing devices. In addition, the system mitigates data poisoning attacks that target individuals' smartphones, edge devices, or cloud servers by utilizing blockchain to store contacts, delegations, and identities.INDEX TERMS Edge computing, infectious diseases, COVID-19, blockchain, pandemic contact tracing

Privacy-preserving COVID-19 contact tracing solution based on blockchain

“…However, [33] and ours both do not consider any location data into the tracing framework and can only achieve passive security in the semi-honest model. Inspired by the work of [39] , where edge servers are utilized to assist medical authorities for contact tracing in the malicious model, we hope to take the public and private location (i.e., businesses, houses, and offices) data into tracing approach and achieve a much better tracing solution with higher-level security in the future.…”

Elevating Security Measures in Cyber-Physical Systems: Deep Neural Network-Based Anomaly Detection with Ethereum Blockchain for Enhanced Data Integrity

“…In [7], the focus was on health experts tracing users who opt out or are impotent to engage in contact locating, proposing a solution utilizing edge servers that reduces power usage by end-users up to 97%.…”

“…The process of simulation uses MATLAB software version 2018R. For the validation of the algorithm, it employed two intrusion detection datasets, such as the NSL-KDD 2015 and CIDDS-001 datasets[7]. The NSL-KDD dataset involves 125,973 instances with 41 characteristics and two classes, whereas the CIDDS-001 dataset encompasses 1,018,950 instances by 14 attributes and two classes.…”

Predicting High-Risk Individuals in Disease Outbreaks Using Fuzzy Logic-Based Contact Tracing Model.

“…The proposed system uses edge servers to assist in tracking users that withdraw from using contact tracing. Edge computing devices are location-based data collectors; therefore they can be used in notifying users without disclosing the identities of the individuals [32]. Panja el al.…”