• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5159-5178
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• 2018

Network Intrusion detection is a rapidly growing field of information security due to its importance for modern IT infrastructure. Many supervised and unsupervised learning techniques have been devised by researchers from discipline of machine learning and data mining to achieve reliable detection of anomalies. In this paper, a deep convolutional neural network (DCNN) based intrusion detection system (IDS) is proposed, implemented and analyzed. Deep CNN core of proposed IDS is fine-tuned using Randomized search over configuration space. Proposed system is trained and tested on NSLKDD training and testing datasets using GPU. Performance comparisons of proposed DCNN model are provided with other classifiers using well-known metrics including Receiver operating characteristics (RoC) curve, Area under RoC curve (AuC), accuracy, precision-recall curve and mean average precision (mAP). The experimental results of proposed DCNN based IDS shows promising results for real world application in anomaly detection systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.945-948
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• 2005

현재 침입탐지시스템(IDS:Intrusion Detection System)은 다양한 평가요소들 - 탐지율, 오탐율, 새로운 공격탐지능력, 안정성 등을 기준으로 평가되고 있고, 이러한 결과는 제품의 보호수준을 결정하거나 한 조직의 정보보호장치로 적합한지를 평가하는 벤치마킹테스트의 방법으로 활용된다. 그러나, 이러한 평가의 결과는 조직의 침입탐지시스템을 구축하고자 하는 네트워크 환경하에서 각각의 침입탐지시스템이 갖는 특성에 따라 상대적인 평가는 가능하나 해당 조직의 네트워크 인프라와 위협요소, 취약점을 고려했을 때 보다 최적의 것이 무엇인지를 평가하는 방법으로는 한계가 있다. 그러므로, 본 연구논문에서는 이러한 한계를 극복하기 위한 방법으로서 조직의 정보보호 위험분석에서 도출된 해당 네트워크 환경의 자산, 위협, 취약성의 결과인 위험과 위험수준을 IDS 평가에 반영하여 조직의 환경하에 보다 적합한 침입탐지시스템 선정이 가능한 평가방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.2213-2216
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• 2003

단일 호스트 환경에 특화되어 설계되어온 기존 침입탐지 시스템(Intrusion Detection System: IDS)은 침입 시 도메인의 보호만을 그 목적으로 하는 수동적인 성격으로써, 새로운 공격 기법에 대한 탐지 및 대응, 그리고 보다 그 규모가 큰 네트워크로의 확장 면에서 구조적인 결함을 가지고 있다. 이러한 IDS의 구조적 문제점의 해결방안으로 액티브 네트워크 기반의 IDS 에 관한 연구가 진행되고 있다. 액티브 네트워크(Active network)란 패킷 스위칭 네트워크 상에 프로그램 가능한 라우터 등인 액티브 노드들을 배치하고, 사용자의 요구에 상응하는 적절한 연산을 위한 데이터와 프로그램으로 구성된 스마트 패킷(smart packet)에 대하여 수행 가능하게 하는 접근 방법이다. 본 논문에서는 이를 기반으로 자율적이며 지능적인 에이전트로 구성된 멀티 에이전트 기술을 액티브 노드에 적용함으로써 기존 IDS 보안메커니즘에서 보다 러 진보된 능동적이고 적극적인 대응을 위한 보안 메커니즘을 제공하여 네트워크 공격에 의한 피해 최소화와 신속한 대응이 가능한 멀티 에이전트 기반 공격 대응 메커니즘을 제시하고, 이를 적용 가능한 액티브 네트워크 기반 프레임 설계를 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.88-92
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• 2004

Most studies in the past in testing and benchmarking on Intrusion Detection System (IDS) were conducted as comparisons, rather than evaluation, on different IDSs. This paper presents the evaluation of the performance of one of the open source IDS, snort, in an inexpensive high availability system configuration. Redundancy and fault tolerance technology are used in deploying such IDS, because of the possible attacks that can make snort exhaust resources, degrade in performance and even crash. Several test data are used in such environment and yielded different results. CPU speed, Disk usage, memory utilization and other resources of the IDS host are also monitored. Test results with the proposed system configuration environment show much better system availability and reliability, especially on security systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.10 no.1
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• pp.39-52
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• 2000

컴퓨터망의 확대 및 컴퓨터 이용의 급격한 증가에 따른 부작용으로 컴퓨터 보안 문제가 중요하게 대두되고 있다. 이에 따라 침입자들로부터 침입을 줄이기 위한 침입탐지시스템에 관한 연구가 활발하다. 본 논문에서는 컴퓨터 면역 시스템을 바탕으로 한 새로운 IDS 모델을 제안하고, 이를 설계하고 프로토타입을 구현하는 그 타당성을 보인다. 제안한 모델에서 IDS들은 여러 컴퓨터에 분산되고, 분산된 IDS들 중 어느 하나가 특권 프로세스(Privilege process)에 의해 발생된 시스템 호출 순서 중 비정상적인 시스템 호출을 탐지한 경우 이를 다른 IDS들과 서로 동적으로 공유하여 새로운 침입에 대한 면역력을 향상시킨다.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.67-74
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• 2022

One type of network security breach is the availability breach, which deprives legitimate users of their right to access services. The Denial of Service (DoS) attack is one way to have this breach, whereas using the Intrusion Detection System (IDS) is the trending way to detect a DoS attack. However, building IDS has two challenges: reducing the false alert and picking up the right dataset to train the IDS model. The survey concluded, in the end, that using a real dataset such as MAWILab or some tools like ID2T that give the researcher the ability to create a custom dataset may enhance the IDS model to handle the network threats, including DoS attacks. In addition to minimizing the rate of the false alert.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.1-12
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• 2022

Besides unexpected growth perceived by IoT's, the variety and volume of threats have increased tremendously, making it a necessity to introduce intrusion detections systems for prevention and detection of such threats. But Intrusion Detection and Prevention System (IDPS) inside the IoT network yet introduces some unique challenges due to their unique characteristics, such as privacy inference, performance, and detection rate and their frequency in the dynamic networks. Our research is focused on the privacy inferences of existing intrusion prevention and detection system approaches. We also tackle the problem of providing unified a solution to implement the open-source IDPS in the IoT architecture for assessing the performance of IDS by calculating; usage consumption and detection rate. The proposed scheme is considered to help implement the human health monitoring system in IoT networks

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.131-141
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• 2009

An increasing variety of malware, such as worms, spyware and adware, threatens both personal and business computing. Remotely controlled bot networks of compromised systems are growing quickly. This paper proposes an intrusion detection system based outflow traffic analysis. Many research efforts and commercial products have focused on preventing intrusion by filtering known exploits or unknown ones exploiting known vulnerabilities. Complementary to these solutions, the proposed IDS can detect intrusion of unknown new mal ware before their signatures are widely distributed. The proposed IDS is consists of a outflow detector, user monitor, process monitor and network monitor. To infer user intent, the proposed IDS correlates outbound connections with user-driven input at the process level under the assumption that user intent is implied by user-driven input. As a complement to existing prevention system, proposed IDS decreases the danger of information leak and protects computers and networks from more severe damage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.584-587
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• 2012

MANET, which can be constructed with only terminal devices, has structural advantages of ease installation and operation, also has environmental change of rapid supply of smart phone, it's usage can be extended to application area likes as emergency communication, leasure, exploration and investigations. But, as one characteristic of MANET, no use of communicaton infrastructure caused disadvantage of weakness for information intrusion which is frequently occurred, nowadays. In this paper, the effects of IDS(Intrusion Detection System), one of defence tools for information intrusion, is analyzed for transmission performance. Blackhole attack is assumed as a type of intrusion, MANET defence with IDS from intrusions. Computer simulation based on NS-2 used for performance measurement. In this paper, performance measurement is done for application service to analyze application level effects of IDS. VoIP service is used as application service.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.609-616
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• 2005

Signature-based Intrusion Detection has many false positive and many difficulties to detect new and changed attacks. Alpha-cut is introduced which reduces false positive with a combination of signature-based IDS and machine learning-based IDS in prior paper [1]. This research is a study of a succession of Alpha-cut, and we introduce Beta-rick in which attacks can be detected but cannot be detected in single signature-based detection. Alpha-cut is a way of increasing detection accuracy for the signature based IDS, Beta-pick is a way which decreases the case of treating attack as normality. For Alpha-cut and Beta-pick we use XIBL as a learning algorithm and also show the difference of result of Sd.5. To describe the value of proposed method we apply Alpha-cut and Beta-pick to signature-based IDS and show the decrease of false alarms.