Users of electronic devices, e.g., laptop, smartphone, etc. have characteristic behaviors while surfing the Web. Profiling this behavior can help identify the person using a given device. In this paper, we introduce a technique to profile users based on their web transactions. We compute several features extracted from a sequence of web transactions and use them with one-class classification techniques to profile a user. We assess the efficacy and speed of our method at differentiating 25 users on a dataset representing 6 months of web traffic monitoring from a small company network.
@article{arxiv.1703.09745,
title = {Profiling Users by Modeling Web Transactions},
author = {Radek Tomsu and Samuel Marchal and N. Asokan},
journal= {arXiv preprint arXiv:1703.09745},
year = {2017}
}
Comments
Extended technical report of an IEEE ICDCS 2017 publication