Research Article
Classification of Hidden Users’ Profiles in Wireless Communications
@INPROCEEDINGS{10.1007/978-3-642-30422-4_1, author={Eduardo Rocha and Paulo Salvador and Ant\^{o}nio Nogueira}, title={Classification of Hidden Users’ Profiles in Wireless Communications}, proceedings={Mobile Networks and Management. Third International ICST Conference, MONAMI 2011, Aveiro, Portugal, September 21-23, 2011, Revised Selected Papers}, proceedings_a={MONAMI}, year={2012}, month={9}, keywords={User Profiling Web-Application Identification Wireless Networks Wavelet Decomposition Scalograms}, doi={10.1007/978-3-642-30422-4_1} }- Eduardo Rocha
Paulo Salvador
António Nogueira
Year: 2012
Classification of Hidden Users’ Profiles in Wireless Communications
MONAMI
Springer
DOI: 10.1007/978-3-642-30422-4_1
Abstract
The Internet can be seen as a mix of several services and applications running on top of common protocols. The emergence of several web-applications changed the users’ interaction paradigm by placing them in a more active role allowing them to share photos, videos and much more. The analysis of the profile of each user, both in wired and wireless networks, becomes very interesting for tasks such as network resources optimization, service personalization and security. In this paper, we propose a promiscuous wireless passive monitoring classification approach that can accurately create users’ profiles in terms of the used web-applications and does not require authentication with the wireless Access Point. By extracting appropriate layer 2 traffic metrics, performing a Wavelet Decomposition and analyzing the obtained scalograms, it is possible to analyze the traffic’s time and frequency components. An appropriate communication profile can then be defined in order to describe this frequency spectrum which is characteristic to each web-based application. Consequently, it is possible to identify the applications that are being used by the different connected clients and build user-profiles. Wireless traffic generated by several connected clients running some of the most significant web-based applications was captured and analyzed and the obtained results show that it is possible to obtain an accurate application traffic mapping and an accurate user profiling.
