• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.361-363
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• 2004

서비스 거부(denial of service) 공격의 일종인 SYN flooding 공격은 TCP/IP 프로토콜의 오류로 인해 발생한다. 기존의 SYN flooding 해결 연구들은 대부분 방화벽이나 라우터에서 패킷을 감시하여 불법적으로 판단된 패킷을 걸러내는 방법을 사용하였다. 따라서 기존의 연구들은 방화벽이나 라우터에 많은 부하를 주게 된다. 본 연구에서는 방화벽이나 라우터의 도움을 받지 않고, 기존의 네트워크 환경이나 운영체제에 큰 변화를 가하지 않으면서, 서버 시스템 자체만으로 SYN flooding 공격에 효율적으로 대응할 수 있는 방법을 제시하고자 한다.

• ETRI Journal
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• v.44 no.2
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• pp.346-354
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• 2022

The SYN flooding attack is widely used in cyber attacks because it paralyzes the network by causing the system and bandwidth resources to be exhausted. This paper proposed a self-information approach for detecting the SYN flooding attack and provided a detection algorithm with a hierarchical policy on a detection time domain. Compared with other detection methods of entropy measurement, the proposed approach is more efficient in detecting the SYN flooding attack, providing low misjudgment, hierarchical detection policy, and low time complexity. Furthermore, we proposed a detection algorithm with limiting system resources. Thus, the time complexity of our approach is only (log n) with lower time complexity and misjudgment rate than other approaches. Therefore, the approach can detect the denial-of-service/distributed denial-of-service attacks and prevent SYN flooding attacks.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.148-153
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• 2003

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.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.55-66
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• 2009

In this paper, I will discuss how the Internet has spread rapidly in our lives. Large portals and social networks experience service attacks that access personal customers' databases. This interferes with normal service through DDoS (Distribute Denial of Service Attack), which is the topic I want to discuss. Among the types of DDoS, TCP SYN Flooding attacks are rarely found because they use few traffics and its attacking type is regular transaction. The purpose of this study is to find and suggest the method for accurate detection of the attacks. Through the analysis of TCP SYN Flooding attacks, we find that these attacks cause Backscatter effect. This study is about the algorithm which detects the attacks of TCP SYN Flooding by the study of Backscatter effect.

• Convergence Security Journal
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• v.23 no.5
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• pp.73-79
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• 2023

Cyber threats are evolving and becoming more sophisticated with the development of new technologies, and consequently the number of service failures caused by DDoS attacks are continually increasing. Recently, DDoS attacks have numerous types of service failures by applying a large amount of traffic to the domain address of a specific service or server. In this paper, after generating the data of the Syn Flooding attack, which is the representative attack type of bandwidth exhaustion attack, the data were compared and analyzed using Random Forest, Decision Tree, Multi-Layer Perceptron, and KNN algorithms for the effective detection of attacks, and the optimal algorithm was derived. Based on this result, it will be useful to use as a technique for the detection policy of Syn Flooding attacks.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.35-41
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• 2015

SDN(Software Defined Networking) has been considered as a new future computer network architecture and DDoS(Distributed Denial of Service) is the biggest threat in the network security. In SDN architecture, we present the technique to defend the DDoS SYN Flooding attack that is one of the DDoS attack method. First, we monitor the Backlog queue in order to reduce the unnecessary monitoring resources. If the Backlog queue of the certain server is occupied over 70%, the sFlow performs packet sampling with the server address as the destination address. To distinguish between the attacker and the normal user, we use the source address. We decide the SYN packet threshold using the remaining Backlog queue that possible to allow the number of connections. If certain sources address send the SYN packet over the threshold, we judge that this address is attacker. The controller will modify the flow table entry to block attack traffics. By using this method, we reduce the resource consumption about the unnecessary monitoring and the protection range is expanded to all switches. The result achieved from our experiment show that we can prevent the SYN Flooding attack before the Backlog queue is fully occupied.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.2045-2048
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• 2003

서비스 거부공격(DoS Attack : Denial-of-Service Attack)이란 공격자가 침입대상 시스템의 시스템 자원과 네트워크 자원을 대량으로 소모시킴으로써 정상 사용자로 하여금 시스템이 제공하는 서비스를 하지 못하도록 하는 공격을 의미한다. TCP SYN Flooding 기법을 이용한 DoS공격은 서비스 자체를 하지 못하도록 하기 보다는 다른 공격을 하기 위한 사전 공격으로써 활용될 소지가 높은 공격법인 것이다. 본 논문에서는 TCP SYN Flooding을 이용한 DoS공격의 근본적인 원인을 분석하고 시스템 보안 관리자의 입장에서 이 공격에 능동적으로 탐지 할 수 있는 해결책을 모색해보고자 한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.660-663
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• 2003

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 Fuzzy Cognitive Maps(FCM) that can detect intrusion by the Denial of Service(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 Sp flooding Preventer using Fuzzy cognitive maps(SPuF) model captures and analyzes the packet information 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. The result of simulating the "KDD ′99 Competition Data Set" in the SPuF model shows that the Probe detection rates were over 97 percentages.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.988-994
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• 2014

Software Defined Network (SDN) is a new technology in computer network area which enables user to centralize control plane. The security issue is important in computer network to protect system from attackers. SYN flooding attack is one of Distributed Denial of Service attack methods which are popular to degrade availability of targeted service on Internet. There are many methods to protect system from attackers, i.e. firewall and IDS. Even though firewall is designed to protect network system, but it cannot mitigate DDoS attack well because it is not designed to do so. To improve performance of DDOS mitigation we utilize another mechanism by using SDN technology such as OpenFlow and sFlow. The methodology of sFlow to detect attacker is by capturing and sum cumulative traffic from each agent to send to sFlow collector to analyze. When sFlow collector detect some traffics as attacker, OpenFlow controller will modify the rule in OpenFlow table to mitigate attacks by blocking attack traffic. Hence, by combining sum cumulative traffic use sFlow and blocking traffic use OpenFlow we can detect and mitigate SYN flooding attack quickly and cheaply.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.491-498
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• 2003

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.