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 WeberAuthors Info & Claims
Justin Hummel, Andrew McDonald, Vatsal Shah, Riju Singh, Bradford D. Boyle, Tingshan Huang, Nagarajan Kandasamy, Harish Sethu, Steven WeberAuthors Info & ClaimsPages 135 - 138
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.
Supplementary Material
The attached zip archive contains a PDF version of the poster to be presented at CODASPY 2014.
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References
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Index Terms
- A modular multi-location anonymized traffic monitoring tool for a WiFi network
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Information & Contributors
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Published In
March 2014
368 pages
ISBN:9781450322782
DOI:10.1145/2557547
- General Chairs:
- Elisa Bertino,
- Ravi Sandhu,
- Program Chair:
- Jaehong Park
Copyright © 2014 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
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Published: 03 March 2014
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CODASPY'14
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CODASPY'14: Fourth ACM Conference on Data and Application Security and Privacy
March 3 - 5, 2014
Texas, San Antonio, USA
Acceptance Rates
CODASPY '14 Paper Acceptance Rate 19 of 119 submissions, 16%;
Overall Acceptance Rate 149 of 789 submissions, 19%
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