מיכאל פייר

אקדמי בכיר

Detecting anomalous behaviors using structural properties of social networks

Yaniv Altshuler, Michael Fire, Erez Shmueli, Yuval Elovici, Alfred Bruckstein, Alex Pentland, David Lazer

In this paper we discuss the analysis of mobile networks communication patterns in the presence of some anomalous "real world event". We argue that given limited analysis resources (namely, limited number of network edges we can analyze), it is best to select edges that are located around 'hubs' in the network, resulting in an improved ability to detect such events. We demonstrate this method using a dataset containing the call log data of 3 years from a major mobile carrier in a developed European nation.

שפת פרסום אנגלית
דפים 433-440
סטטוס פרסום פורסם - 14.03.2013

Keywords

Anomalies Detection
Behavior Modeling
Emergencies
Mobile Networks

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science
גישה למסמך
10.1007/978-3-642-37210-0_47
קבצים וקישורים אחרים
Link to publication in Scopus