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서비스 거부 공격에서의 퍼지인식도를 이용한 네트워크기반의 지능적 침입 방지 모델에 관한 연구
이세열,김용수,심귀보,Lee, Se-Yul,Kim, Yong-Soo,Sim, Kwee-Bo 한국지능시스템학회 2003 한국지능시스템학회논문지 Vol.12 No.2
서비스 거부 공격은 침입을 위한 침입시도 형태로 나타나며 대표적인 공격으로 Syn Flooding 공격이 있다. Syn Flooding 공격은 신뢰성 및 연결 지향적 전송서비스인 TCP의 종단간에 3-way handshake의 취약점을 이용한 공격이다. 본 논문에서는 네트워크 기반의 지능적 침입 방지 모델을 제안한다. 제안하는 모델은 Syn Flooding 공격을 탐지하기 위하여 패킷 정보를 수집하고 분석한다. 이 모델은 퍼지인식도(Fuzzy Cognitive Maps)를 적용한 결정모듈의 분석 결과를 활용하여 서비스 거부 공격의 위험도를 측정하고 공격에 대응하도록 대응모듈을 학습시킨다. 제안하는 모델은 Syn Flooding 공격의 위험을 격감 또는 방지하는 네트워크 기반의 지능적 침입 방지 모델이다. A DoS(Denial of Service) attack appears in the form of the intrusion attempt and Syn Flooding attack is a typical example. The Syn Flooding attack takes advantage of the weak point of 3-way handshake between the end-points of TCP which is the connection-oriented transmission service and has the reliability This paper proposes a NIIP(Network based Intelligent Intrusion Prevention) model. This model captures and analyzes the packet informations for the detection of Syn Flooding attack. Using the result of analysis of decision module, the decision module, which utilizes FCM(Fuzzy Cognitive Maps), measures the degree of danger of the DoS and trains the response module to deal with attacks. This model is a network based intelligent intrusion prevention model that reduces or prevents the danger of Syn Flooding attack.
A Ntoe on Bayes Risks of Estimators
이세열 제주대학교 1984 논문집 Vol.17 No.-
The Bayes estimation theory is based on the prior space, the sample space, the loss function and the posterior distribution, etc. In this paper we observe some loss functions which are concerned with mean, median and mode of the posterior distribution of the parameter, and we derive, using the predictive distribution and the posterior distribution, the retation of Bayes risks.
On Steepest Descent for Linear Operator Equations
이세열,김도현 제주대학교 1984 논문집 Vol.17 No.-
In this paper, we establish the convergence of the method of steepest descent to a solution of any equation, for any initial approximation x_(o). We also show that the method converges to the unique solution with minimal norm if and only if x_(o) is in the range of any adjoint operator.
TCP 프로토콜을 사용하는 서비스거부공격 탐지를 위한 침입시도 방지 모델
이세열,김용수,Lee, Se-Yul,Kim, Yong-Soo 한국지능시스템학회 2003 한국지능시스템학회논문지 Vol.14 No.7
The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using FCM(Fuzzy Cognitive Maps) that can detect intrusion by the DoS attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The SPuF(Syn flooding Preventer using Fussy cognitive maps) model captures and analyzes the packet informations to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance comparison, the "KDD′99 Competition Data Set" made by MIT Lincoln Labs was used. The result of simulating the "KDD′99 Competition Data Set" in the SPuF model shows that the probe detection rates were over 97 percentages.
서비스 거부 공격에서의 퍼지인식도를 이용한 네트워크기반의 지능적 침입 방지 모델에 관한 연구
이세열,김용수,심귀보 한국지능시스템학회 2003 한국지능시스템학회논문지 Vol.11 No.3
A DoS(Denial of Service) attack appears in the form of the intrusion attempt and Syn Flooding attack is a typical example. The Syn Flooding attack takes advantage of the weak point of 3-way handshake between the end-points of TCP which is the connection-oriented transmission service and has the reliability. This paper proposes a NIIP(Network based Intelligent Intrusion Prevention) model. This model captures and analyzes the packet informations for the detection of Syn Flooding attack. Using the result of analysis of decision module, the decision module, which utilizes FCM(Fuzzy Cognitive Maps), measures the degree of danger of the DoS and trains the response module to deal with attacks. This model is a network based intelligent intrusion prevention model that reduces or prevents the danger of Syn Flooding attack. 서비스 거부 공격은 침입을 위한 침입시도 형태로 나타나며 대표적인 공격으로 Syn Flooding 공격이 있다. Syn Flooding 공격은 신뢰성 및 연결 지향적 전송서비스인 TCP의 종단간에 3-way handshake의 취약점을 이용한 공격이다. 본 논문에서는 네트워크 기반의 지능적 침입 방지 모델을 제안한다. 제안하는 모델은 Syn Flooding 공격을 탐지하기 위하여 패킷 정보를 수집하고 분석한다. 이 모델은 퍼지인식도(Fuzzy Cognitive Maps)를 적용한 결정모듈의 분석 결과를 활용하여 서비스 거부 공격의 위험도를 측정하고 공격에 대응하도록 대응모듈을 학습시킨다. 제안하는 모델은 Syn Flooding 공격의 위험을 격감 또는 방지하는 네트워크 기반의 지능적 침입 방지 모델이다.
서비스 거부 공격에서의 퍼지인식도를 이용한 네트워크 기반 침입탐지시스템
이세열,김용수 大田大學校 産業技術硏究所 2002 산업기술연구소 論文集 Vol.13 No.2
Recently the attacks using the vulnerabilities of networks have been increasing. These attacks appear in the form. of the intrusion attempts and Denial of Service is a typical example. This paper proposes NIID(Network based Intelligent Intrusion Detection) model that reduces or prevents the danger of Denial of Service Attack. This model captures and analyzes the packet informations to detect the Syn Flooding Attack among Denial of Service Attacks. The Syn Flooding Attack takes advantange of the weak point of 3-way handshake between the end-points of TCP and connection-oriented transmission service. Using the result of analyses this model, which utilizes FCM(Fuzzy Cognitive Maps), measures the degree of danger of the Denial of Service Attack and adapts the response module to deal with attacks.