• Proceedings of the Korea Society for Simulation Conference
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• 2001.05a
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• pp.72-76
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• 2001

인터넷이 생활의 중요한 요소로 자리잡기 시작하면서 네트워크의 침해 사고가 급증하고 있는 현실이다. 이러한 침해 사고를 예방하기 위해 침입 탐지 시스템(IDS)과 방화벽(Firewall)이 많이 사용되고 있다. 방화벽과 침입 탐지 시스템은 연동은 서로의 단점을 보완하여 더 강력하게 네트워크를 보호할 수 있다. 방화벽과 침입 탐지 시스템을 위한 시뮬레이션 모델은 DEVS (Discrete Event system Specification) 방법론을 사용하여 구성하였다. 본 논문에서는 실제 침입 데이터를 발생시켜 실제 침입에 가까운 상황 가운데 침입 행위를 판별하도록 구성하였다. 이렇게 구성된 시뮬레이션 모델을 사용하여 침입탐지 시스템의 핵심 요소인 침입 판별이 효과적으로 수행되는지를 시뮬레이션 할 수 있다. 현재의 침입은 광범위해지고, 복잡하게 되어 한 침입 탐지 시스템이 독립적으로 네트워크의 침입을 판단하기 어렵게 되었다. 이를 위해 네트워크 내에 여러 침입 탐지 시스템 에이전트를 배치하였고, 에이전트들이 서로 정보를 공유함으로써 공격에 효과적으로 대응할 수 있도록 하였다. 침입 탐지 시스템이 서로 협력하여 침입을 탐지하고, 이런 정보를 침입 차단 시스템에게 넘겨주게 된다. 이와 같은 구성을 통해서 공격자로부터 발생된 패킷이 네트워크 내로 들어오는 것을 원천적으로 막을 수 있도록 하였다.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.235-242
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• 2004

As e-business being rapidly developed the importance of security is on the rise in network. Intrusion detection systems which are a core security system detect the network intrusion trial. As intrusions become more sophisticated, it is beyond the scope of any one IDS to deal with them. Thus we placed multiple IDS agents in the network and the information helpful for detecting the intrusions is shared among these agents to cope effectively with attackers. Each agent cooperates through the BBA (Black Board Architecture) and CNP (Contract Net Protocol) for detecting intrusions. In this paper, we propose the effective method comparing the blackboard architecture to contract net protocol.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.974-987
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• 2005

As the ad hoc networks have been received a great deal of attention to not only the military but also the industry applications, some security mechanisms are required for implementing a practical ad hoc application. In this paper, we propose a security architecture in ad hoc networks for the purpose of supporting ID-based public key cryptosystems because of the advantage that ID-based schemes require less complex infrastructure compared with the traditional public key cryptosystems. We assume a trusted key generation center which only issues a private key derived from IDs of every nodes in the system setup phase, and use NIL(Node ID List) and NRL(Node Revocation List) in order to distribute the information about IDs used as public keys in our system. Furthermore, we propose a collaborative status checking mechanism that is performed by nodes themselves not by a central server in ad-hoc network to check the validity of the IDs.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.217-219
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• 2017

나날이 증가하는 해킹의 위협에 따라 이를 방어하기 위한 침임 탐지 시스템과 로그 수집 분야에서 많은 연구가 진행되고 있다. 이러한 연구들로 인해 다양한 종류의 침임 탐지 시스템이 생겨났으며, 이는 다양한 종류의 침입 탐지 시스템에서 서로의 단점을 보안할 필요성이 생기게 되었다. 따라서 본 논문에서는 네트워크 기반인 NIDS(Network-based IDS)와 호스트 기반인 HIDS(Host-based IDS)의 장단점을 가진 Hybrid IDS을 구성하기 위해 NIDS와 HIDS의 로그 데이터 통합을 위해 실시간 로그 처리에 특화된 Kafka를 이용하고, 실시간 분석에 Spark Streaming을 이용하여 통합된 로그를 분석하게 되며, 실시간 전송 도중에 발생되는 데이터 유실에 대해 별도로 저장되는 Hadoop의 HDFS에서는 데이터 유실에 대한 보장을 하는 실시간 Hybrid IDS 분석 시스템에 대한 설계를 제안한다.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.373-379
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• 1999

This paper investigates the subject of intrusion detection over networks. Existing network-based IDS's are categorised into three groups and the overall architecture of each group is summarised and assessed. A new methodology to this problem is then presented, which is inspired by the human immune system and based on a novel artificial immune model. The architecture of the model is presented and its characteristics are compared with the requirements of network-based IDS's. The paper concludes that this new approach shows considerable promise for future network-based IDS's

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.373-379
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• 1999

This pqer investigates the subject of intrusion detection over networks. Existing network-based IDS's are categorised into three groups and the overall architecture of each group is summarised and assessed. A new methodology to this problem is then presented, which is inspired by the human immune system and based on a novel artificial immune model. The architecture of the model is presented and its characteristics are compared with the requirements of network-based IDS's. The paper concludes that this new approach shows considerable promise for future network-based IDS's.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8C
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• pp.748-757
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• 2002

Cyber-terror trials are increased in nowadays and these attacks are commonly using security vulnerability and information gathering method by variable services grew by the continuous development of Internet Technology. IDS's application environment is affected by this increasing Cyber Terror. General Network based IDS detects intrusion by signature based Intrusion Detection module about inflowing packet through network devices. Up to now security in network is commonly secure host, an regional issue adopted in special security system but these system is vulnerable intrusion about the attack in globally connected Internet systems. Security mechanism should be produced to expand the security in whole networks. In this paper, we analyzer the DARPA's program and study Infusion Detection related Technology. We design policy security framework for policy enforcing in whole network and look at the modules's function. Enforcement of security policy is acted by Intrusion Detection system on gateway system which is located in network packet's inflow point. Additional security policy is operated on-line. We can design and execute central security policy in managed domain in this method.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1077-1082
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• 2016

IDS can be used as a countermeasure for malicious attacks which cause degrade of network transmission performance by disturbing of MANET routing function. In this paper, effects of IDS for transmission performance on MANET under grayhole attacks which has intrusion objects for a part of transmissions packets, some suggestion for effective IDS will be considered. Computer simulation based on NS-2 is used for performance analysis, performance is measured with VoIP(: Voice over Internet Protocol) as an application service. MOS(: Mean Opinion Score), CCR(: Call Connection Rate) and end-to-end delay is used for performance parameter as standard transmission quality factor for voice transmission.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.542-547
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• 2003

A network based intrusion detection system(N-IDS), can detect intruders coming in through packets in real time environment. The ability of capture of packet is the most important factor when we evaluate the performance of the system. The time delay between the time handling one packet capture and next one is variant become of packet handling mechanism. So for N-IDS can not settle this problem because most systems use a single processor. In this thesis, we solve the problem of irregular tine delay with a file socket and multi-thread processing. We designed and implement, the Crasto system. By an accurate observation, the performance testing shows that the Crasto reduces the capture delay time to 1/5 comparing to the existing single process N-IDS, and maintain delay time regularly.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.411-418
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• 2020

In the field of information security, IDS(Intrusion Detection System) is normally classified in two different categories: signature-based IDS and anomaly-based IDS. Many studies in anomaly-based IDS have been conducted that analyze network traffic data generated in cyberspace by machine learning algorithms. In this paper, we studied pre-processing methods to overcome performance degradation problems cashed by rare classes. We experimented classification performance of a Machine Learning algorithm by reconstructing data set based on rare classes and semi rare classes. After reconstructing data into three different sets, wrapper and filter feature selection methods are applied continuously. Each data set is regularized by a quantile scaler. Depp neural network model is used for learning and validation. The evaluation results are compared by true positive values and false negative values. We acquired improved classification performances on all of three data sets.