• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.391-394
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• 2004

Change of paradigm of network attack technique was begun by fast extension of the latest Internet and new attack form is appearing. But, Most intrusion detection systems detect informed attack type because is doing based on misuse detection, and active correspondence is difficult in new attack. Therefore, to heighten detection rate for new attack pattern, visibilitys to apply human immunity mechanism are appearing. In this paper, we create self-file from normal behavior profile about network packet and embody self recognition algorithm to use self-nonself discrimination in the human immune system to detect anomaly behavior. Sense change because monitors self-file creating anomaly detector based on Negative Selection Algorithm that is self recognition algorithm's one and detects anomaly behavior. And we achieve simulation to use DARPA Network Dataset and verify effectiveness of algorithm through the anomaly detection rate.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.29-39
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• 2006

With the increasing popularity of the wireless network, the vulnerability issue on IEEE 802.1x Wireless Local Area Network (WLAN) are more serious than we expected. Security issues range from mis-configured wireless Access Point(AP) such as session hijacking to Denial of Service(DoS) attack. We propose a new system based on intrusion detection or prevention mechanism to protect the wireless network against these attacks. The proposed system has a security solution on AP that includes an intrusion detection and protection system(IDS/IPS) as an embedded module. In this paper, we suggest integrated wireless IDS/IPS module on AP with wireless traffic monitoring, analysis and packet filtering module against malicious wireless attacks. We also present that the system provides both enhanced security and performance such as on the university wireless campus network.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.15-23
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• 2021

In most hacking attacks, hackers intrudes inside for a long period of time and attempts to communicate with the outside using a circumvent connection to achieve purpose. research in response to advanced and intelligent cyber threats has been mainly conducted with signature-based detection and blocking methods, but recently it has been extended to threat hunting methods. attacks from organized hacking groups are advanced persistent attacks over a long period of time, and bypass remote attacks account for the majority. however, even in the intrusion detection system using intelligent recognition technology, it only shows detection performance of the existing intrusion status. therefore, countermeasures against targeted bypass rwjqthrwkemote attacks still have limitations with existing detection methods and threat hunting methods. in this paper, to overcome theses limitations, we propose a model that can detect the targeted circumvent connection remote attack threat of an organized hacking group. this model designed a threat hunting process model that applied the method of verifying the origin IP of the remote circumvent connection, and verified the effectiveness by implementing the proposed method in actual defense information system environment.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06c
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• pp.304-306
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• 2006

21세기 정보혁명을 바탕으로 전쟁의 양상은 정보전, 네트워크 및 컴퓨터 중심의 사이버전과 같은 새로운 전쟁 패러다임으로 변화하고 있다. 이러한 정보전에 대비하여 국방정보체계에 다양한 정보보호시스템을 설치하여 사용하고 있다. 그러나 국방정보체계 환경에 현재까지 배치된 정보보호시스템들은 침해 사고에 대한 탐지 및 보고 등의 수동적인 대응만을 지원한다. 그러므로 발생한 공격에 대한 대응을 마련하더라도 동일한 공격자가 동일한 목표 시스템에 대하여 또 다른 공격 기술을 이용하여 재침입이 가능하다. 이를 방어하기 위하여 공격에 대한 능동적인 대응이 필요하다. 대표적인 능동 대응 기술인 침입자 역추적은 시스템 및 네트워크에 대하여 공격을 시도하는 침입자의 네트워크 상의 실제 위치를 추적하는 기술이다. 침해 사고를 근본적으로 차단하기 위하여 침입자의 실제 신분 확인이 필수적이다. 이를 위하여 본 논문에서는 침입자 역추적 기술을 분석하고 국방정보체계 환경을 위한 세션분석기반의 침입자 역추적 기술을 제안한다. 또한 이 기술을 기반으로 구현한 침입자 역추적 시스템을 소개한다.

• Convergence Security Journal
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• v.19 no.4
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• pp.181-188
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• 2019

Recently, attempts to apply artificial intelligence technology to create the normal profile in Anomaly-based intrusion detection systems have been made actively. But existing studies that proposed the application of artificial intelligence technology mostly focus on improving the structure of artificial neural networks and finding optimal hyper-parameter values, and fail to address various problems that may arise from the misconfiguration of learning data. In this paper, we identify the main problems that may arise due to the misconfiguration of learning data through experiment. And we also propose a novel approach that can address such problems and improve the detection performance through reconstruction of learning data.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.301-303
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• 2004

인터넷의 급성장으로 해킹이나 Dos 공격, 웜, 바이러스 등의 사이버 범죄가 크게 증가하고 지능화되어 최근 역추적에 대한 관심이 날로 증가하고 있다. 보안 도구로 침입탐지시스템(IDS) 이나 침입방지시스템 (IPS) 등이 있으나 해킹이나 DoS 공격을 방어하는데 현실적으로 한계가 있다. 따라서 능동적인 해킹 방어를 위한 기본적인 기술로 해커의 실제 위치를 추적하는 역추적 시스템 기술이 필요하다. 특히 IPv4에서의 역추적 시스템에 대한 연구는 활발하게 이루어지고 있지만 IPv6에 대한 연구는 아직 미흡하다. 본 논문에서는 IPv4의 주소 고갈로 인해 앞으로 이를 대신할 IPv6에 대한 공격 근원지 역추적 시스템 개발이 시급하다고 보고. 해킹을 시도하는 해커의 실제 위치를 실시간으로 추적할 수 있도록 IPv6 헤더 패킷의 트래픽 클래스(Traffic Class)와 플로우 라벨(Flow Label)을 이용하여 IPv6에서의 실시간 네트워크 침입자 역추적 시스템 모델을 제안하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.169-174
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• 2003

The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.411-416
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• 2002

Recently, the trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online internet, so it is expected to make a problem more and more. Currently, the general security system based on Internet couldn't cope with the attack properly, if ever, other regular systems have depended on common softwares to cope with the attack. In this paper, we propose the positive selection mechanism and negative selection mechanism of T-cell, which is the biological distributed autonomous system, to develop the self/non-self recognition algorithm, the anomalous behavior detection algorithm, and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. The proposed algorithm can cope with new intrusion as well as existing one to intrusion detection system in the network environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.412-415
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• 2004

As computers and networks become popular, corporation or country organization composes security network including various kinds information protection system to protect informations and resources from internet and is operating system and network. But current firewall and IDS(Intrusion Detection System) of the network level suffers from many vulnerabilities in internal computing informations and resources. In this paper, we design of ICMP-based Traceback System using a ICMP Traceback Message for efficiently traceback without change structure of routers. ICMP-based Traceback System. Create of ICMP message is managed by “Traceback Agent” mirroring port for router. Victim's systems that are received the message store it and “Traceback Manager” is detect a attack(like a DDoS). Using a information of this message starting a traceback and detecting a source of attacker, so response a attack.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.5
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• pp.69-78
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• 2004

The change of attack techniques paradigm was begun by fast extension of the latest Internet and new attack form appearing. But, Most intrusion detection systems detect only known attack type as IDS is doing based on misuse detection, and active correspondence is difficult in new attack. Therefore, to heighten detection rate for new attack pattern, the experiments to apply various techniques of anomaly detection are appearing. In this paper, we propose an behavior profiling method using Bayesian framework based on graphics from audit data and visualize behavior profile to detect/analyze anomaly behavior. We achieve simulation to translate host/network audit data into BF-XML which is behavior profile of semi-structured data type for anomaly detection and to visualize BF-XML as SVG.