Conference proceeding
A modular multi-location anonymized traffic monitoring tool for a WiFi network
Proceedings of the 4th ACM conference on data and application security and privacy, pp 135-138
03 Mar 2014
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.
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Details
- Title
- A modular multi-location anonymized traffic monitoring tool for a WiFi network
- Creators
- Justin Hummel - Drexel UniversityAndrew McDonald - Drexel UniversityVatsal Shah - Drexel UniversityRiju Singh - Drexel UniversityBradford Boyle - Drexel UniversityTingshan Huang - Drexel UniversityNagarajan Kandasamy - Drexel UniversityHarish Sethu - Drexel UniversitySteven Weber - Drexel UniversityRajveer Singh - Civil, Architectural, and Environmental Engineering
- Publication Details
- Proceedings of the 4th ACM conference on data and application security and privacy, pp 135-138
- Conference
- 4th ACM conference on data and application security and privacy, 4th
- Series
- CODASPY '14
- Publisher
- Association for Computing Machinery (ACM)
- Number of pages
- 1
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; Computer Science; Civil, Architectural, and Environmental Engineering
- Scopus ID
- 2-s2.0-84898928036
- Other Identifier
- 991019173570504721