• 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.

• 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 the Korea Institute of Information Security & Cryptology
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• v.14 no.2
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• pp.113-121
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• 2004

In a result that the types of intrusion detection are getting diverse in accordance with rapid internet sprawl, many intrusion detection systems have been developed. In this paper, we will propose a novel evaluation on the evaluation criteria for the intrusion detection systems using Fuzzy integrals

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.8-16
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• 2003

This paper moses a method to solve the weakness in Snort, the network based intrusion detection system. Snort which is the rule-based intrusion detection system dose not supports a protection method for their own rules which are signatures to detect intrusions. Therefore the purpose of this paper is to provide a scheme for protecting rules. The system with the proposed scheme could support integrity and confidentiality to the rules.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.727-738
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• 2003

Much research efforts are being exerted for the study of intrusion detection system(IDS). However little work has been for the communication medels and performance eveluation of the IDS. Here we present a communication framework for doing hybrid intrusion detection in which agents are used for local intrusion detections with a centralized data anaysis componenta for a global intrusion detection at multiple domains environment. We also assume the combination of host-based and network-based intrusion detection systems in the oberall framework. From the local domain, a set of information such as alert, and / or log data are reported to the upper level. At the root of the hierarchy, there is a global manager where data coalescing is performed. The global manager delivers a security policy to its lower levels as the result of aggregation and correlation of intrusion detection alerts. In this paper, we model the communication mechanisms for the hybrid IDS and develop a simular using OPNET modeller for the performance evaluation of transmission capabillities for the delivery of data and policy. We present and compare simulation results based on several scenarios focuding on communication delay.

• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.119-132
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• 2006

The network based security techniques well-known until now have week points to be passive in attacks and susceptible to roundabout attacks so that the misuse detection based intrusion prevention system which enables positive correspondence to the attacks of inline mode are used widely. But because the Misuse detection based Intrusion prevention system is proportional to the detection rules, it causes excessive false alarm and is linked to wrong correspondence which prevents the regular network flow and is insufficient to detect transformed attacks, This study suggests an Intrusion prevention system which uses Support Vector machines(hereinafter referred to as SVM) as one of rule based Intrusion prevention system and Anomaly System in order to supplement these problems, When this compared with existing intrusion prevention system, show performance result that improve about 20% and could through intrusion prevention system that propose false positive minimize and know that can detect effectively about new variant attack.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.279-282
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• 2006

네트워크를 기반으로 한 컴퓨터 시스템이 현대 사회에 있어서 더욱 더 불가결한 역할을 하는 것에 따라, 네트워크 기반 컴퓨터 시스템은 침입자의 침입 목표가 되고 있다. 이를 보호하기 위한 침입탐지시스템(Intrusion Detection System : IDS)은 점차 중요한 기술이 되었다. 침입탐지시스템에서 패턴들을 분석한 후 정상/비정상을 판단 및 예측하기 위해서는 초기단계인 특징추출이나 선택이 매우 중요한 부분이 되고 있다. 본 논문에서는 IDS에서 중요한 부분인 feature selection을 Data Mining 기법인 Genetic Algorithm(GA)과 Decision Tree(DT)를 적용해서 구현했다.

• Convergence Security Journal
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• v.5 no.3
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• pp.33-41
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• 2005

Information can be leaked, changed, damaged and illegally used regardless of the intension of the information owner. Intrusion Detection Systems and Firewalls are used to protect the illegal accesses in the network. But these are the passive protection method, not the active protection method. They only react based on the predefined protection rules or only report to the administrator. In this paper, we develop the intrusion detection and protection system using Netfilter framework. The system makes the administrator's management easy and simple. Furthermore, it offers active protection mechanism against the intrusions.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.1
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• pp.75-82
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• 2003

Computer and network security has recently become a popular subject due to the explosive growth of the Internet Especially, attacks based on malformed packet are difficult to detect because these attacks use the skill of bypassing the intrusion detection system and Firewall. This paper designs and implements a network-based intrusion detection system (NIDS) which detects intrusions with malformed-packets in real-time. First, signatures, rules in NIDS like Snouts rule files, are classified using similar properties between signatures NIDS creates a rule tree applying hashing technique based on the classification. As a result the system can efficiently perform intrusion detection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.5
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• pp.684-688
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• 2002

One of the Problems, which the Intrusion Detection System has, is a False Positive. This False make to low condition of the Intrusion Detection System. The cause of the False Positive is that the learning is not enough during audit data learning steps. Therefore, in this paper, 1 propose the method of the Intrusion Detection System that be learnt audit data to agent with association rule.