Abstract
Computational cost is one of the major concerns of the commercial Intrusion Detection Systems (IDSs). Although these systems are proven to be promising in detecting network attacks, they need to check all the signatures to identify a suspicious attack in the worst case. This is time consuming. This paper proposes an efficient two-tier IDS, which applies a statistical signature approach and a Linear Discriminant Method (LDM) for the detection of various Web-based attacks. The two-tier system converts high-dimensional feature space into a low-dimensional feature space. It is able to reduce the computational cost and integrates groups of signatures into an identical signature. The integration of signatures reduces the cost of attack identification. The final decision is made on the integrated low-dimensional feature space. Finally, the proposed two-tier system is evaluated using DARPA 1999 IDS dataset for webbased attack detection.
Original language | Undefined |
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Title of host publication | Information and Communications Security |
Place of Publication | Berlin |
Publisher | Springer |
Pages | 459-471 |
Number of pages | 13 |
DOIs | |
Publication status | Published - 2010 |
Event | 12th International Conference on Information and Communications Security, ICICS 2010 - Barcelona, Spain Duration: 15 Dec 2010 → 17 Dec 2010 Conference number: 12 |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer Verlag |
Volume | 6476 |
ISSN (Print) | 0302-9743 |
Conference
Conference | 12th International Conference on Information and Communications Security, ICICS 2010 |
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Abbreviated title | ICICS |
Country | Spain |
City | Barcelona |
Period | 15/12/10 → 17/12/10 |
Keywords
- SCS-Cybersecurity
- EWI-25352
- Packet payload
- IR-92854
- Feature Selection
- Linear discriminant method
- Web-based attack
- Intrusion Detection