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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