Yong-Hee Jeon

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BcN(Broadband convergence Networks) is being deployed in order to support a variety of network applications such as E-Commerce, DMB(Digital Multimedia Broadcasting), Home Network, VoIP(Voice over IP), and other services. As network bandwidth is growing rapidly and services are converged, the opportunity and severity of network intrusions are growing as(More)
In this paper, we propose an intrusion detection system(IDS) architecture which can detect and respond against the generation of abnormal traffic such as malicious code and Internet worms. We model the system, design and implement a simulator using OPNET Modeller, for the performance analysis on the response capacity of alert information in the proposed(More)
BcN(Broadband convergence Network) is being deployed in order to support a variety of network applications, with enhanced capabilities of QoS(Quality of Service) provisioning and security, and IPv6. In a high-speed network environment such as BcN, it is more likely for the network resources to be exposed to various intrusion activities. The propagation(More)
Many Network Intrusion Detection System(NIDS)s have been developed to detect and respond against several kinds of intrusion activities in widespread networks. Due to the explosive growth of network bandwidth, software approach in developing a high-speed NIDS is becoming impractical due to the performance constraint. Accordingly, it seems unavoidable to(More)
This paper proposes Gigabit IDS to detect and respond against various attacks on high-speed links. Our proposed system has hardware-based stateful intrusion detection architecture that can provide the high-performance detection mechanism. It is possible through the pattern matching and heuristic analysis functions that are processed in FPGA Logic. In this(More)
1. Abstract This research is accomplished for the validation that it is possible to evaluate reliability and robustness simultaneously under uncertainty with an approximated model. For this, Monte Carlo Simulation and an artificial neural network were used as implements to obtain the probabilistic and stochastic properties, such as expectation and standard(More)
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