A high-throughput system architecture for deep packet filtering in network intrusion prevention
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, D.Y. | - |
dc.contributor.author | Kim, S. | - |
dc.contributor.author | Choi, L. | - |
dc.contributor.author | Kim, H. | - |
dc.date.accessioned | 2022-02-07T07:41:55Z | - |
dc.date.available | 2022-02-07T07:41:55Z | - |
dc.date.created | 2022-02-07 | - |
dc.date.issued | 2006 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/25009 | - |
dc.description.abstract | Pattern matching is one of critical parts of Network Intrusion Prevention Systems (NIPS). Pattern matching hardware for NIPS should find a matching pattern at wire speed. However, that alone is not good enough. First, pattern matching hardware should be able to generate sufficient pattern match information including the pattern index number and the location of the match found at wire speed. Second, it should support pattern grouping to reduce unnecessary pattern matches. Third, it should show constant worst-case performance even if the number of patterns is increased. Finally it should be able to update patterns in a few minutes or seconds without stopping its operations. We modify Shift-OR hardware accelerator and propose a system architectures to meet the above requirement. Using Xilinx FPGA simulation, we show the new system scaled well to achieve a high speed over 10Gbps and satisfies all of the above requirements. © Springer-Verlag Berlin Heidelberg 2006. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Springer Verlag | - |
dc.title | A high-throughput system architecture for deep packet filtering in network intrusion prevention | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, S. | - |
dc.identifier.doi | 10.1007/11682127_29 | - |
dc.identifier.scopusid | 2-s2.0-33745602206 | - |
dc.identifier.bibliographicCitation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.3894 LNCS, pp.407 - 421 | - |
dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.volume | 3894 LNCS | - |
dc.citation.startPage | 407 | - |
dc.citation.endPage | 421 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
94, Wausan-ro, Mapo-gu, Seoul, 04066, Korea02-320-1314
COPYRIGHT 2020 HONGIK UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.