The user attribution problem and the challenge of persistent surveillance of user activity in complex networks

In telecommunication networks, the user attribution problem refers to the challenge faced in recognizing communication traffic as belonging to a given user when information needed to identify the user is missing. This problem becomes more difficult to tackle as users move across many mobile networks (complex networks) owned and operated by different providers. The traditional approach of using the source IP address as a tracking identifier does not work when used to identify mobile users. Recent efforts to address this problem by exclusively relying on web browsing behavior to identify users, brought to light the challenges of solutions which try to link up multiple user sessions together when these approaches rely exclusively on the frequency of web sites visited by the user. This study has tackled this problem by utilizing behavior based identification while accounting for time and the sequential order of web visits by a user. Hierarchical Temporal Memories (HTM) were used to classify historical navigational patterns for different users. This approach enables linking multiple user sessions together forgoing the need for a tracking identifier such as the source IP address. Results are promising. HTMs outperform traditional Markov chains based approaches and can provide high levels of identification accuracy.