| Publisher | Massachusetts Institute of Technology | ||
|---|---|---|---|
| Format | 131.5KB PDF | Date added | 16 Feb 2004 |
| Topics | TCP - IP | ||
| Downloads | 1 | ||
Using probabilistic learning, a naive Bayesian classifier to passively infer a host's operating system from packet headers is developed. The authors analyze traffic captured from an Internet exchange point and compare this classifier to rule-based inference tools. While the host operating system distribution is heavily skewed, the authors found operating systems that constitute a small fraction of the host count contribute a majority of total traffic. Finally as an application of this classifier, the number of hosts masquerading behind NAT devices is counted and results against prior techniques are evaluate.
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