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2024
 Campo-Vázquez, Celeste;  García-Rubio, Carlos;  Jimenez-Berenguel, Andrea;  Moure-Garrido, Marta;  Almenares-Mendoza, Florina;  Díaz-Sánchez, Daniel
Inferring mobile applications usage from DNS traffic Proceedings Article 
In: Ad Hoc Networks, Elsevier B.V., 2024.
Abstract | Links | BibTeX | Tags: compromise, dns traffic, I-Shaper, mobile applications identification, Qursa, user privacy
@inproceedings{campo012,

title = {Inferring mobile applications usage from DNS traffic},

author = {Celeste Campo-Vázquez and Carlos García-Rubio and Andrea Jimenez-Berenguel and Marta Moure-Garrido and Florina Almenares-Mendoza and Daniel Díaz-Sánchez },

url = {https://www.sciencedirect.com/science/article/pii/S1570870524002129#d1e710},

doi = {https://doi.org/10.1016/j.adhoc.2024.103601},

year  = {2024},

date = {2024-07-19},

urldate = {2024-07-19},

booktitle = {Ad Hoc Networks},

publisher = {Elsevier B.V.},

abstract = {In the digital era, our lives are intrinsically linked to the daily use of mobile applications. As a consequence, we generate and transmit a large amount of personal data that puts our privacy in danger. Despite having encrypted communications, the DNS traffic is usually not encrypted, and it is possible to extract valuable information from the traffic generated by mobile applications. This study focuses on the analysis of the DNS traffic behavior found in mobile application traces, developing a methodology capable of identifying mobile applications based on the domains they query. With this methodology, we were able to identify apps with 98% accuracy. Furthermore, we have validated the effectiveness of the characterization obtained with one dataset by identifying traces from other independent datasets. The evaluation showed that the methodology provides successful results in identifying mobile applications.},

keywords = {compromise, dns traffic, I-Shaper, mobile applications identification, Qursa, user privacy},

pubstate = {published},

tppubtype = {inproceedings}

}

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In the digital era, our lives are intrinsically linked to the daily use of mobile applications. As a consequence, we generate and transmit a large amount of personal data that puts our privacy in danger. Despite having encrypted communications, the DNS traffic is usually not encrypted, and it is possible to extract valuable information from the traffic generated by mobile applications. This study focuses on the analysis of the DNS traffic behavior found in mobile application traces, developing a methodology capable of identifying mobile applications based on the domains they query. With this methodology, we were able to identify apps with 98% accuracy. Furthermore, we have validated the effectiveness of the characterization obtained with one dataset by identifying traces from other independent datasets. The evaluation showed that the methodology provides successful results in identifying mobile applications.
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https://www.sciencedirect.com/science/article/pii/S1570870524002129#d1e710
doi:https://doi.org/10.1016/j.adhoc.2024.103601
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