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http://dx.doi.org/10.17662/ksdim.2017.13.3.019

An Hybrid Probe Detection Model using FCM and Self-Adaptive Module  

Lee, Seyul (청운대학교 컴퓨터학과)
Publication Information
Journal of Korea Society of Digital Industry and Information Management / v.13, no.3, 2017 , pp. 19-25 More about this Journal
Abstract
Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.
Keywords
Cloud; FCM; Hybrid Probe; IoT; SAM;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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