MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation

MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation

Citation Author(s):
Giuseppe
Aceto
University of Napoli Federico II
Domenico
Ciuonzo
University of Napoli Federico II
Antonio
Montieri
University of Napoli Federico II
Valerio
Persico
University of Napoli Federico II
Antonio
Pescapè
University of Napoli Federico II
Submitted by:
Antonio Montieri
Last updated:
Mon, 10/07/2019 - 10:02
DOI:
10.21227/maj9-vh13
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Network traffic analysis, i.e. the umbrella of procedures for distilling information from network traffic, represents the enabler for highly-valuable profiling information, other than being the workhorse for several key network management tasks. While it is currently being revolutionized in its nature by the rising share of traffic generated by mobile and hand-held devices, existing design solutions are mainly evaluated on private traffic traces, and only a few public datasets are available, thus clearly limiting repeatability and further advances on the topic. To this end, we have designed and implemented MIRAGE, a reproducible architecture for mobile-app traffic capture and ground-truth creation. The outcome of this system is MIRAGE-2019, a human-generated dataset for mobile traffic analysis (with associated ground-truth) having the goal of advancing the state-of-the-art in mobile app traffic analysis. MIRAGE-2019 is expected to be capitalized by the networking community for different tasks related to mobile traffic analysis.

Instructions: 

MIRAGE-2019 is a human-generated dataset for mobile traffic analysis with associated ground-truth, having the goal of advancing the state-of-the-art in mobile app traffic analysis. MIRAGE-2019 takes into consideration the traffic generated by more than 280 experimenters using 40 mobile apps via 3 devices.

A sampled version of the dataset (one app per category) is readily downloadable, whereas the complete version is available on request.

APP LIST reports the details on the apps contained in the two versions of the dataset.

If you are using MIRAGE-2019 human-generated dataset for scientific papers, academic lectures, project reports, or technical documents, please help us increasing its impact by citing the following reference:

Giuseppe Aceto, Domenico Ciuonzo, Antonio Montieri, Valerio Persico and Antonio Pescapè,"MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation",4th IEEE International Conference on Computing, Communications and Security (ICCCS 2019), October 2019, Rome (Italy).

[ARTICLE] [BIBTEX]

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[1] , "MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/maj9-vh13. Accessed: Oct. 14, 2019.
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, 2019. MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation. Available at: http://dx.doi.org/10.21227/maj9-vh13.
. (2019). "MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation." Web.
1. . MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/maj9-vh13
. "MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation." doi: 10.21227/maj9-vh13