An Algorithm for Intrusion Prevention System based on Fuzzy Connectedness Clustering
draft-yang-ipsfcc-algorithm-00
| Document | Type |
Expired Internet-Draft
(individual)
Expired & archived
|
|
|---|---|---|---|
| Author | Yixian Yang | ||
| Last updated | 2005-10-21 | ||
| RFC stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
Abstract
In this document, an algorithm for intrusion prevention systems based on fuzzy connectedness clustering was presented in order to measure the similarity. Fuzzy connectedness that was first applied in image segmentation was extended to clustering algorithm, and used as the similarity metric between objects to be clustered. By a little expert knowledge, starting with at least one seed data in each cluster, the similarity between each data in dataset and each seed data in each cluster was measured. According to the highest fuzzy connectedness of each data, clustering was finished. This algorithm was applied in intrusion prevention systems as a tool of detecting intrusion, overcoming some shortcomings of previous clustering algorithm.
Authors
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