A modular multi-location anonymized traffic monitoring tool for a WiFi network

Authors:
Justin Hummel;Andrew McDonald;Vatsal Shah;Riju Singh;Bradford D. Boyle;Tingshan Huang;Nagarajan Kandasamy;Harish Sethu;Steven Weber
Affiliations:
Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA
Venue:
Proceedings of the 4th ACM conference on Data and application security and privacy
Year:
2014

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Abstract

Network traffic anomaly detection is now considered a surer approach to early detection of malware than signature-based approaches and is best accomplished with traffic data collected from multiple locations. Existing open-source tools are primarily signature-based, or do not facilitate integration of traffic data from multiple locations for real-time analysis, or are insufficiently modular for incorporation of newly proposed approaches to anomaly detection. In this paper, we describe DataMap, a new modular open-source tool for the collection and real-time analysis of sampled, anonymized, and filtered traffic data from multiple WiFi locations in a network and an example of its use in anomaly detection.