Integration Soft Computing Approach to Network Security
| dc.contributor.author | Surat Srinoy | |
| dc.contributor.correspondence | S. Srinoy; Computer Science Department, Suan Dusit Rajabhat University, Bangkok, 295 Ratchasima Rd, Thailand; email: surat_sri@dusit.ac.th | |
| dc.date.accessioned | 2025-03-10T07:38:08Z | |
| dc.date.available | 2025-03-10T07:38:08Z | |
| dc.date.issued | 2007 | |
| dc.description.abstract | Computer security is defined as the protection of computing system against threats to confidentiality, integrity, and availability. Due to increasing incidents of cyber attacks, building effective intrusion detection systems are essential for protecting information systems security. It is an important issue for the security of network to detect new intrusion attack and also to increase the detection rates and reduce false positive rates in this area. Lacking a distinctive boundary definition among normal and abnormal datasets, discriminating the normal and abnormal behaviors seems too much complex. This paper proposes an integrating support vector machine and rough set for recognizing intrusion detection in computer network. Empirical results clearly show that support vector machine and rough set approach could play a major role for intrusion detection systems. © 2007 IEEE. | |
| dc.identifier.citation | Proceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007 | |
| dc.identifier.doi | 10.1109/AMS.2007.55 | |
| dc.identifier.isbn | 0769528457; 978-076952845-8 | |
| dc.identifier.scopus | 2-s2.0-84963938754 | |
| dc.identifier.uri | https://repository.dusit.ac.th//handle/123456789/5056 | |
| dc.language | English | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.rights.holder | Scopus | |
| dc.title | Integration Soft Computing Approach to Network Security | |
| dc.type | Conference paper | |
| mods.location.url | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963938754&doi=10.1109%2fAMS.2007.55&partnerID=40&md5=20a7d8a6e8bfdf324bf46e98f8225915 | |
| oaire.citation.endPage | 164 | |
| oaire.citation.startPage | 159 |