An empirical assessment of global COVID-19 contact tracing applications
| dc.contributor.author | Sun, R. | |
| dc.contributor.author | Wang, W. | |
| dc.contributor.author | Xue, M. | |
| dc.contributor.author | Tyson, G. | |
| dc.contributor.author | Camtepe, S. | |
| dc.contributor.author | Ranasinghe, D.C. | |
| dc.contributor.conference | IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) (25 May 2021 - 28 May 2021 : virtual online) | |
| dc.date.issued | 2021 | |
| dc.description | Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering: Companion Proceedings (ICSE-Companion 2021) | |
| dc.description.abstract | This is the artifact accompanying the paper “An Empirical Assessment of Global COVID-19 Contact Tracing Applications”, accepted by ICSE 2021. The artifact presents the first automated security and privacy assessment tool that tests contact tracing apps for security weaknesses, malware, embedded trackers and private information leakage. COVIDGUARDIAN outperforms 4 state-of-the-practice industrial and open-source tools. Note that, Although the tool is tailored to focus on contact tracing apps, it can also be adapted to other types of apps with respect to the NLP PII learning context, e.g., by changing the source & sink list or updating the sensitive PII keywords. | |
| dc.description.statementofresponsibility | Ruoxi Sun, Wei Wang, Minhui Xue, Gareth Tyson, Seyit Camtepe, and Damith C. Ranasinghe | |
| dc.identifier.citation | International Conference on Software Engineering, 2021, pp.173-174 | |
| dc.identifier.doi | 10.1109/ICSE-Companion52605.2021.00074 | |
| dc.identifier.isbn | 9781665412193 | |
| dc.identifier.issn | 2574-1926 | |
| dc.identifier.issn | 2574-1934 | |
| dc.identifier.orcid | Sun, R. [0000-0001-5404-8550] | |
| dc.identifier.orcid | Xue, M. [0000-0001-5411-5039] [0000-0002-9172-4252] | |
| dc.identifier.orcid | Ranasinghe, D.C. [0000-0002-2008-9255] | |
| dc.identifier.uri | https://hdl.handle.net/2440/132545 | |
| dc.language.iso | en | |
| dc.publisher | IEEE | |
| dc.relation.ispartofseries | Proceedings / IEEE/ACM International Conference on Software Engineering Companion | |
| dc.rights | ©2021 IEEE | |
| dc.source.uri | https://ieeexplore.ieee.org/xpl/conhome/9402220/proceeding | |
| dc.title | An empirical assessment of global COVID-19 contact tracing applications | |
| dc.type | Conference item | |
| pubs.publication-status | Published |