• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.43-53
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• 2007

Intrusion detection system(IDS) has recently evolved while combining signature-based detection approach with anomaly detection approach. Although signature-based IDS tools have been commonly used by utilizing machine learning algorithms, they only detect network intrusions with already known patterns, Ideal IDS tools should always keep the signature database of your detection system up-to-date. The system needs to generate the signatures to detect new possible attacks while monitoring and analyzing incoming network data. In this paper, we propose a new outlier cluster detection algorithm with density (or influence) function, Our method assumes that an outlier is a kind of cluster with similar instances instead of a single object in the context of network intrusion, Through extensive experiments using KDD 1999 Cup Intrusion Detection dataset. we show that the proposed method outperform the conventional outlier detection method using Euclidean distance function, specially when attacks occurs frequently.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.331-338
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• 2001

With the general use of network, cyber terror rages throughout the world. However, IP Fragmentation isn\`t free from its security problem yet, even though it guarantees effective transmission of the IP package in its network environment. Illegal invasion could happen or disturb operation of the system by using attack mechanism such as IP Spoofing, Ping of Death, or ICMP taking advantage of defectiveness, if any, which IP Fragmentation needs improving. Recently, apart from service refusal attack using IP Fragmentation, there arises a problem that it is possible to detour packet filtering equipment or network-based attack detection system using IP Fragmentation. In the paper, we generate the real time access log file to make the system manager help decision support and to make the system manage itself in case that some routers or network-based attack detection systems without packet reassembling function could not detect or suspend illegal invasion with divided datagrams of the packet. Through the implementation of the self-managing system we verify its validity and show its future effect.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.04a
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• pp.387-390
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• 2001

최근 세계적으로 유수한 인터넷 사이트들의 해킹으로 인해 네트워크 보안의 중요성이 강조되고 있다. 네트워크 보안을 위해 방화벽보다는 좀더 신뢰성이 높은 네트워크 및 시스템에 대한 보안 솔루션으로 침입 탐지 시스템(Intrusion Detection System)이 차세대 보안 솔루션으로 부각되고 있다. 본 논문에서는 기존의 IDS의 단점이었던 호스트 레벨에서 확장된 분산환경에서의 실시간 침입 탐지는 물론 이기종간의 시스템에서도 탐지가 가능한 새로운 IDS 모델을 제안 설계하였다. 그리고, 프로토타입을 구현하여 그 타당성을 검증하였다. 이를 위해 서로 다른 이기종에서 분산 침입 탐지에 필요한 강사 파일을 자동적으로 추출하기 위해서 패턴 추출 에이전트를 이용하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.4
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• pp.29-39
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• 2002

In general, the intrusion detection method of anomalous behaviors has high false alarm rate which contains false-positive and false-negative. To increase the sensitivity of intrusion detection, we propose a method of aggregate detection to reduce false alarm rate by using correlation between misuse activity detection sensors and anomalous ones. For each normal behavior and anomalous one, we produce the reflection rate between the result from one sensor and another in off-line. Then, we apply this rate to the result of real-time detection to reduce false alarm rate.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.157-165
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• 2004

The paper suggests that web-server security management system will be able to detect the web service attack accurately and swiftly which is keeping on increasing at the moment and reduce the possibility of the false positive detection. This system gathers the results of many unit security modules at the real time and enhances the correctness of the detection through the correlation analysis procedure. The unit security module consists of Network based Intrusion Detection System module. File Integrity Check module. System Log Analysis module, and Web Log Analysis and there is the Correlation Analysis module that analyzes the correlations on the spot as a result of each unit security module processing. The suggested system provides the feasible framework of the range extension of correlation analysis and the addition of unit security module, as well as the correctness of the attack detection. In addition, the attack detection system module among the suggested systems has the faster detection time by means of restructuring Snort with multi thread base system. WSM will be improved through shortening the processing time of many unit security modules with heavy traffic.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.777-780
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• 2000

최근 세계적으로 유수한 인터넷 사이트들의 해킹으로 인해 네트워크 보안의 중요성이 강조되고 있다. 네트워크 보안을 위해 방화벽보다는 좀 더 신뢰성이 높은 네트워크 및 시스템에 대한 보안 솔루션으로 침입 탄지 시스템(IDS)이 차세대 보안 솔루션으로 부각되고 있다. 본 논문에서는 기존의 IDS의 단점이었던 호스트 레벨에서 확장된 분산환경에서의 실시간 침입 탐지는 물론 이기종간의 시스템에서도 탐지가 가능한 새로운 IDS 모델을 제안.설계하였다. 그리고, 프로토타입을 구현하여 그 타당성을 검증하였다. 이를 위해 서로 다른 이기종에서 침입 탐지에 필요한 감사 파일을 자동적으로 추출하기 위해서 분산 에이전트를 이용한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.619-622
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• 2002

IDS has been studied mainly in the field of the detection derision and collecting of audit data. The detection decision should decide whether successive behaviors are intrusions or not , the collecting of audit data needs ability that collects precisely data for intrusion decision. Artificial methods such as rule based system and neural network are recently introduced in order to solve this problem. However, these methods have simple host structures and defects that can't detect transformed intrusion patterns. So, we propose the method using data mining agent that can retrieve and estimate the patterns and retrieval of user's behavior in the distributed different hosts.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.121-128
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• 2019

Computing systems have various vulnerabilities to cyber attacks. In particular, various cyber attacks that are intelligent in the information society have caused serious social problems and economic losses. Traditional security systems are based on misuse-based technology, which requires the continuous updating of new attack patterns and the real-time analysis of vast amounts of data generated by numerous security devices in order to accurately detect. However, traditional security systems are unable to respond through detection and analysis in real time, which can delay the recognition of intrusions and cause a lot of damage. Therefore, there is a need for a new security system that can quickly detect, analyze, and predict the ever-increasing cyber security threats based on machine learning and big data analysis models. In this paper, we present a IDS model that combines machine learning and big data technology.

• The KIPS Transactions:PartC
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• v.13C no.3 s.106
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• pp.295-302
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• 2006

An intrusion detection system writes a lot of alarms against attack behaviors in real time. These alarms contain not only actual attack alarms, but also false alarms that are mistakes made by the intrusion detection system. False alarms are the main reason that reduces the efficiency of the intrusion detection system, and we propose framework for false alarms analysis in the paper. Also, we apply an incremental data mining method for pattern analysis of false alarms increasing continuously. The framework consists of GUI, DB Manager, Alert Preprocessor, and False Alarm Analyzer. We analyze the false alarms increasingly through the experiment of the proposed framework and show that false alarms are reduced by applying the analyzed false alarm rules in the intrusion detection system.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.5
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• pp.117-124
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• 2000

As network security is coming up with significant problem after the major Internet sites were hacked nowadays, IDS (Intrusion Detection System) is considered as a next generation security solution for more trusted network and system security We propose the new IDS model which can detect intrusion in the expanded distribute environment in host level, drawback of existing IDS, and implement prototype. We used pattern extraction agent so that we extract automatically audit file needed in intrusion detection even in other Platforms.