There are two main approaches for intrusion detection: signature-based and anomaly-based. Signature-based detection employs pattern matching to match attack signatures with observed data making it ideal for detecting known attacks. However, it cannot detect unknown attacks for which there is no signature available. Anomaly-based detection builds a profile of normal system behavior to detect known and unknown attacks as behavioral deviations. However, it has a drawback of a high false alarm rate. In this thesis, we describe our anomaly-based IDS designed for detecting intrusions in cryptographic and application-level protocols. Our system has several unique characteristics, such as the ability to monitor cryptographic protocols and application-level protocols embedded in encrypted sessions, a very lightweight monitoring process, and the ability to react to protocol misuse by modifying protocol response directly.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc4414 |
| Date | 12 1900 |
| Creators | Joglekar, Sachin P. |
| Contributors | Tate, Stephen R., Mikler, Armin R., Dantu, Ram |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | Text |
| Rights | Public, Copyright, Joglekar, Sachin P., Copyright is held by the author, unless otherwise noted. All rights reserved. |
Page generated in 0.0021 seconds