MIRAGE-COVID-CCMA-2022 takes into consideration the traffic generated by more than 150 experimenters using 9 mobile apps for communication and collaboration via 3 devices. The experimenters used each app to perform at most 3 different user activities.
The dataset is released in two formats, making available both the raw traffic data captured (in JSON format) and a pre-processed version providing the set of inputs (in pickle format) leveraged in our work.
APP LIST reports the details on the apps and related activities contained in the downloadable version of the dataset.
MIRAGE-COVID-CCMA-2022 dataset is released under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
If you are using MIRAGE-COVID-CCMA-2022 human-generated dataset for scientific papers, academic lectures, project reports, or technical documents, please help us increasing its impact by citing the following reference:
Idio Guarino, Giuseppe Aceto, Domenico Ciuonzo, Antonio Montieri, Valerio Persico, Antonio Pescapè,
Contextual Counters and Multimodal Deep Learning for Activity-Level Traffic Classification of Mobile Communication Apps during COVID-19 Pandemic,
Elsevier Computer Networks, Special issue on Machine Learning empowered Computer Networks, 2022.
[ARTICLE] [BIBTEX]