• Convergence Security Journal
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• v.4 no.2
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• pp.1-7
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• 2004

The growth of incidents on the Internet has reflected growth of the internet itself and growth of the computing Power. while in Previous years, external attacks tended to originate from those interested trend in exploring the Internet for its own sake and testing their skills, there is an increasing trend towards intrusions motivated by financial, Political, and military objectives. so, attacks on the nation's computer infrastructures are becoming an increasingly serious problem. Even though the problem is ubiquitious, government agencies are particularly appealing targets and they tend to be more willing to reveal such events than commercial organizations. The threat of damage made necessity of security's recognition, as a result, many researches have been carried out into security of system actively. Intrusion Detection technology is detection of intrusion using audit data differently from using traditional simple filtering and informs manager of it. It has security manager of system deal with the intrusion more quickly. but, cause current environment of Internet manager can't doing response Intrusion alert immediately That's why IPS needed. IPS can response automatically the intrusion alert. so, manager is more comfortable and can response quickly.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.1
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• pp.101-108
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• 2011

The purpose of salinity intrusion due to numerical simulation is analaysis for saline intrusion to the upstream channel in Nakdong River Estuary Barrage(NREB) to get enough fresh water. Conditions that occur salinity intrusion affect by tidal distribution at seas, so salinity concentration changes according to tidal phenomenon. Making this connection cleary can help preventing salinity intrusion. In this study, estimating salinity intrusion to the upstream channel in NREB using EOMSED model, we reexamine NREB's existence. Comparison is also made with observing data. In result, when inflow discharges at $75m^3/s$ is more similar with respect to observing data than $130m^3/s$ at ECOMSED model. Thus, estimations are more precise at little discharges than lots of discharges.

• Journal of Internet Computing and Services
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• v.5 no.5
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• pp.93-103
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• 2004

The main function of the intrusion Detection System (IDS) usee to be more or less passive detection of the intrusion evidences, but recently it is developed with more diverse types and methodologies. Especially, it is required that the IDS should process large system audit data fast enough. Therefore the data mining or neural net algorithm is being focused on, since they could satisfy those situations. In this study, we first surveyed and analyzed the several recent intrusion trends and types. And then we designed and implemented an IDS using back-propagation algorithm of the neural net, which could provide more effective solution. The distinctive feature of our study could be stated as follows. First, we designed the system that allows both the Anomaly dection and the Misuse detection. Second, we carried out the intrusion analysis experiment by using the reliable KDD Cup ‘99 data, which would provide us similar results compared to the real data. Finally, we designed the system based on the object-oriented concept, which could adapt to the other algorithms easily.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.473-482
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• 2007

Network-based IDS(Intrusion Detection System) gathers network packet data and analyzes them into attack or normal. They raise alarm when possible intrusion happens. But they often output a large amount of low-level of incomplete alert information. Consequently, a large amount of incomplete alert information that can be unmanageable and also be mixed with false alerts can prevent intrusion response systems and security administrator from adequately understanding and analyzing the state of network security, and initiating appropriate response in a timely fashion. So it is important for the security administrator to reduce the redundancy of alerts, integrate and correlate security alerts, construct attack scenarios and present high-level aggregated information. False alarm rate is the ratio between the number of normal connections that are incorrectly misclassified as attacks and the total number of normal connections. In this paper we propose a false alarm classification model to reduce the false alarm rate using classification analysis of data mining techniques. The proposed model can classify the alarms from the intrusion detection systems into false alert or true attack. Our approach is useful to reduce false alerts and to improve the detection rate of network-based intrusion detection systems.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3445-3461
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• 2000

Although many different intrusion detectionsystems have been developed there have not been enough researches on the methodology for evaluating these intrusion delection systems. With this understanding,in this paper we present a methodology for evaluating infrusion detection systems from the view point of performance and robustness, both of which are considered the most important criteria Current research on evaluating the performance f intrusion detection systems mostly foduson the in issuse detection but not on the anormaly detection. Regarding evalieting robustness it is not easy to apply off -line methodologies and methods for testing robustness hae not been proposed in on -line methodolomes, In this paper we provide an systematic way of classifyin and generating anomalies and using this reult, present an methodology for evaluating the pertormance of intrusion detection systems in detecting anomaalies ans well as misuses . Moreover, ww study the factors that can damage the robustness of intrusion detection systems and suggest an methodology for assessing the robustness of intrusion detection systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7C
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• pp.971-984
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• 2004

In the coming age of information warfare, information security patterns need to be changed such as to the active approach using offensive security mechanisms rather than traditional passive approach just protecting the intrusions. In an active security environment, it is essential that, when detecting an intrusion, the immediate confrontation such as analysing the intrusion situation in realtime, protecting information from the attacks, and even tracing the intruder. This paper presents an active intrusion-confronting system using a fake session and a honeypot. Through the fake session, the attacks like Dos(Denial of Service) and port scan can be intercepted. By monitoring honeypot system, in which the intruders are migrated from the protected system and an intrusion rule manager is being activated, new intrusion rules are created and activated for confronting the next intrusions.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.391-398
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• 2017

In this paper, we compared the performance of "Network Intrusion Detection System based on attack feature selection using fuzzy control language"[1] and "Intelligent Intrusion Detection System Model for attack classification using RNN"[2]. In this paper, we compare the intrusion detection performance of two techniques using KDD CUP 99 dataset. The KDD 99 dataset contains data sets for training and test data sets that can detect existing intrusions through training. There are also data that can test whether training data and the types of intrusions that are not present in the test data can be detected. We compared two papers showing good intrusion detection performance in training and test data. In the comparative paper, there is a lack of performance to detect intrusions that exist but have no existing intrusion detection capability. Among the attack types, DoS, Probe, and R2L have high detection rate using fuzzy and U2L has a high detection rate using RNN.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.9-15
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• 2018

With the advent of the 5G communication era recently, advancement of the convergence technologies related to IoT has been progressed rapidly. IoT convergence technologies using various sensors are actively applied many fields in our lives, and it contributes to the popularization of these convergence technologies among many people successfully. The security problem of the IoT which connects many things on the network is critically vulnerable and is one of the most important challenge to be solved urgently. In this paper, we design an intrusion detection and self-treatment system for IoT, which can detect external attacks and anomalies in order to solve the security problems in IoT, perform self-treatment by operating the vaccine program according to the intrusion type whenever it detects certain intrusion. Furthermore, we consider the broadcasting of intrusion alarm message according to the frequency of similar circumstances in order to block intrusion contagious in IoT.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.141-149
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• 2013

This paper presents a high-speed intrusion detection process for multi-core video surveillance systems. The high-speed intrusion detection was designed to a parallel process. Based on the analysis of the conventional process, a parallel intrusion detection process was proposed so as to be accelerated by utilizing multiple processing cores in contemporary computing systems. The proposed process performs the intrusion detection in a per-frame parallel manner, considering the data dependency between frames. The proposed process was validated by implementing a multi-threaded intrusion detection program. For the system having eight processing cores, the detection speed of the proposed program is higher than that of the conventional one by up to 353.76% in terms of the frame rate.

• International Journal of Highway Engineering
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• v.6 no.3 s.21
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• pp.47-54
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• 2004

The performance of road-pavement system is closely related to the constituent materials and their susceptibility to mechanical as well as physicochemical stresses. However, the influence of physical and chemical effects on the road-pavement system due to pollution intrusion has not been investigated fully. To study this topic, thu.;, the interaction of a road-pavement system with pollution sources and environments are identified and discussed preliminarily in this paper. Pollution intrusion to road-pavement system occurs by three basic mechanisms; 1) direct intrusion into pavement surface, 2) intrusion from the Right of way, and 3) physical-chemical-biological alterations. Pollution intrusion potential is closely related to material type, particle size, and climatological and topographical features. Stability and performance of road-pavement system is also directly affected by pollution intrusion. Based on these features, thus, engineers working in related to the road design, construction, and maintenance should be seriously considered this topic.