The malicious intrusions to computer systems result in the loss of money, time and hidden information which require deployment of intrusion detection systems. Existing intrusion detection methods analyze packet payload to search for certain strings and to match them with a rule database which takes a long time in large size packets. Because of buffer limits, packets may be dropped or the system may stop working due to high CPU load. In this thesis, we investigate signature based intrusion detection with signatures that only depend on the packet header information without payload inspection. To this end, we analyze the well-known DARPA 1998 dataset to manually extract such signatures and construct a new rule set to detect the intrusions. We implement our rule set in a popular intrusion detection software tool, Snort. Furthermore we enhance our rule set with the existing rules of Snort which do not depend on payload inspection. We test our rule set on DARPA data set as well as a new data set that we collect using attack generator tools. Our results show around 30% decrease in detection time with a tolerable decrease in the detection rate. We believe that our method can be used as a complementary component to speed up intrusion detection systems.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613246/index.pdf |
| Date | 01 May 2011 |
| Creators | Tarim, Mehmet Cem |
| Contributors | Schmidt, Senan Ece |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for METU campus |
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