An Effective Method for Privacy Concerns on Digital Contact Tracing Protocols
5th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2022
; : 1125-1129, 2022.
Article
in English
| Scopus | ID: covidwho-2120576
ABSTRACT
In the post-epidemic era of normalized COVID-19, digital contact tracing will continue to be used as an efficient epidemiological investigation tool. Meanwhile, its widespread use has raised concerns about long-term data privacy and security. In this paper, an effective method for privacy concerns on digital contact tracing protocols (DCTP) is proposed. Digital contact tracing protocols are classified from both technical and architectural perspective. Then, the LINDDUN (each letter of "LINDDUN"stands for a privacy threat type) privacy threat modeling framework is used to analyze the privacy threats that may be contained in different protocols. Last, mitigation strategies are provided to advance privacy protection for future digital contact tracing protocols. The experiment show that the proposed method significantly outperforms existing methods. © 2022 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Language:
English
Journal:
5th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2022
Year:
2022
Document Type:
Article
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