An Overview of Database Centred Intrusion Detection Systems
Ajayi Adebowale1, Idowu S.A2, Otusile Oluwabukola3
1Ajayi Adebowale, Computer Science Department, Babcock University Ilishan Remo, Ogun State, Nigeria.
2Idowu S.A, Computer Science Department, Babcock University Ilishan Remo, Ogun State, Nigeria.
3Otusile Oluwabukola, Computer Science Department, Babcock University Ilishan Remo, Ogun State, Nigeria.
Manuscript received on November 27, 2013. | Revised Manuscript received on December 13, 2013. | Manuscript published on December 30, 2013. | PP: 273-275 | Volume-3, Issue-2, December 2013. | Retrieval Number: B2472123213/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Intrusion detection systems have become a major component of network security infrastructures. Modern day intrusion detection systems are to be reliable, extensible, adaptive to the flow of network traffic and to have a low cost of maintenance. Over the years researchers have looked upon data mining as a means of enhancing the adaptability of an intrusion detection system, as it enables the IDS to discover patterns of intrusions and define valid bounds of network traffic. Despite the effectiveness of data mining based IDS it is riddled with challenges; instrumenting components such as data transformations, model deployment, and cooperative distributed detection remain a labor intensive and complex engineering endeavor. This has lead to research efforts into integrating this technology with traditional database systems. This paper gives an overview of database centered intrusion detection systems.
Keywords: Database systems, Data mining, Intrusion detection systems, Network security.