Conference proceeding
A genetic algorithm for solving the binning problem in networked applications detection
2007 IEEE Congress on Evolutionary Computation, pp 713-720
Sep 2007
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Network administrators need a tool that detects the kind of applications running on their networks, in order to allocate resources and enforce security policies. Previous work shows that applications can be detected by analyzing packet size distributions. Detection by packet size distribution is more efficient and accurate if the distribution is binned. An unbinned packet size distribution considers the occurrences of each packet size individually. In contrast, a binned packet size distribution considers the occurrences of packets within packet size ranges. This paper reviews some of the common methods for binning distributions and presents an improved approach to binning using a genetic algorithms to assist the detection of network applications.
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Details
- Title
- A genetic algorithm for solving the binning problem in networked applications detection
- Creators
- Maxim Shevertalov - Drexel UniversityEdward Stehle - Drexel UniversitySpiros Mancoridis - Drexel University
- Publication Details
- 2007 IEEE Congress on Evolutionary Computation, pp 713-720
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000256053700095
- Scopus ID
- 2-s2.0-79955257809
- Other Identifier
- 991019167703704721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Theory & Methods