Research Article
Profiling and Predicting User Activity on a Home Network
@INPROCEEDINGS{10.4108/eai.7-11-2017.2274043, author={Utku Gunay Acer and Fahim Kawsar and Xueli An}, title={Profiling and Predicting User Activity on a Home Network}, proceedings={14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services}, publisher={ACM}, proceedings_a={MOBIQUITOUS}, year={2018}, month={4}, keywords={internet activity activity prediction network monitoring}, doi={10.4108/eai.7-11-2017.2274043} }- Utku Gunay Acer
Fahim Kawsar
Xueli An
Year: 2018
Profiling and Predicting User Activity on a Home Network
MOBIQUITOUS
ACM
DOI: 10.4108/eai.7-11-2017.2274043
Abstract
This paper reports a study on the characterization of in-home Internet activity behavior based on application usage logs. We collected online activity data from 86 Belgium households for 60 days. We analyzed the activity traces to gain insights on the temporal traffic distribution, interaction regularity, and activity correlations. This analysis is then used to develop a generic method to segment households into designated groups showing similar behavioral profiles. Our technique combines interaction frequencies and regularities across activities for segmentation, and is able to reveal interesting time-slotted profile for each segment. These profiles aim to show the strength of routine behaviors in Internet usage, based on which we present a novel algorithm to predict future Internet activities of a household. Our algorithm shows that 60% of the households online activities can be predicted accurately 70% of times.
