• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.1-7
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• 2012

DDoS attack is a malicious attempt to exhaust resources of target system and network capacities using lots of distributed zombi systems. DDoS attack introduced in early 2000 has being evolved over time and presented in a various form of attacks. This paper proposes a scheme to detect DDoS attacks and to reduce possibility of such attacks that are especially based on vulnerabilities presented by using control packets of existing network protocols. To cope with DDoS attacks, the proposed scheme utilizes a buffer management techniques commonly used for congestion control in Internet. Our scheme is not intended to detect DDoS attacks perfectly but to minimize possibility of overloading of internal system and to mitigate possibility of attacks by discarding control packets at the time of detecting DDoS attacks. In addition, the detection module of our scheme can adapt dynamically to instantly increasing traffic unlike previously proposed schemes.

• Convergence Security Journal
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• v.9 no.4
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• pp.7-12
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• 2009

It is very difficult to completely block the DDoS attack, which paralyzes services by depleting resources or occupying the network bandwidth by transmitting a vast amount of traffic to the specific website or server from normal users' PCs that have been already infected by an outside attacker. In order to defense or endure the DDoS attack, we usually use various solutions such as IDS (Intrusion Detection System), IPS (Intrusion Prevention System), ITS (Intrusion Tolerance System), FW (Firewall), and the dedicated security equipment against DDoS attack. However, diverse types of security appliances cause the cost problem, besides, the full function of the equipments are not performed well owing to the unproper setting without considering connectivity among systems. In this paper, we present the effective connectivity of security equipments and countermeasure methodology against DDoS attack. In practice, it is approved by experimentation that this designed methdology is better than existing network structure in the efficiency of block and endurance. Therefore, we would like to propose the effective security control measures responding and enduring against discriminated DDoS attacks through this research.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.157-163
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• 2009

With the wide usage of internet in many fields, networks are being exposed to many security threats, such as DDoS attack and worm/virus. For enterprise network, prevention failure of network security causes the revealing of commercial information or interruption of network services. In this paper, we propose a method of prevention of DDoS attacks for enterprise network based on traceback and network traffic analysis. The model of traceback implements the detection of IP spoofing attacks by the cooperation of trusted adjacent host, and the method of network traffic analysis implements the detection of DDoS attacks by analyzing the traffic characteristic. Moreover, we present the result of the experiments, and compare the method with other methods. The result demonstrates that the method can effectively detect and block DDoS attacks and IP spoofing attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.809-817
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• 2012

One of the OSI 7 Layer DDoS Attack, HTTP POST DDoS can deny legitimate service by web server resource depletion. This Attack can be executed with less network traffic and legitimate TCP connections. Therefore, It is difficult to distinguish DDoS traffic from legitimate users. In this paper, I propose an anomaly HTTP POST traffic detection algorithm and http each page Content-Length field size limit with defense method for HTTP POST DDoS attack. Proposed method showed the result of detection and countermeasure without false negative and positive to use the r-u-dead-yet of HTTP POST DDoS attack tool and the self-developed attack tool.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.189-194
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• 2005

Present hacking technology is undergone a change on the distributed DoS Attack which cause a lot of traffic to the network or single host. In this paper, with giving mobility to the mean deviation per protocol and it's field, and with adapting pattern matching approach to DDoS attack detection technique, we propose a method to detect the DDoS attack, to have less misdetection and to detect these attacks correctly.

• The Journal of the Korea Contents Association
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• v.4 no.1
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• pp.49-55
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• 2004

DDoS is an attack type that interfere with normal service by running out network bandwidth, process throughput, and system resource. It can be recognized intuitively by network slowdown and connection impossibility state, but it is necessary to detect DDoS attack by exact and quantitative analysis. In this paper, the exact and efficient DDoS attack detection system which is able to detect traffic flooding by MIB information, and attack traffic by packet analysis is proposed and realized.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.1007-1010
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• 2004

본 논문에서는 분산 서비스거부 공격(DDoS)이 발생할 때 네트워크 트래픽의 특성을 분석하기 위해서 트래픽 비율분석법(TRA: Traffic Rate Analysis)을 제안하고 트래픽 비율분석법을 통해서 분석된 다양한 유형의 DDoS 공격의 특성을 기계학습(Machine Learning)을 이용해서 DDoS 공격의 탐지규칙을 생성하고 그 성능을 측정하였다. 트래픽 비율분석법은 감시대상 네트워크 트래픽에서 특정한 유형의 트래픽의 발생비율을 나타내며 TCP flag rate 와 Protocol rate 로 구분된다. 트래픽 비율분석법을 적용한 결과 각각의 DDoS 공격 유형에 따라서 매우 독특한 특성을 가짐을 발견하였다. 그리고, 분석된 데이터를 대상으로 세 개의 기계학습 방법(C4.5, CN2, Na?ve Bayesian Classifier)을 이용해서 DDoS 공격의 탐지규칙을 생성하여 DDoS 공격의 탐지에 적용했다. 실험결과, 본 논문에서 제안된 트래픽 비율분석법과 기계학습을 통한 DDoS 공격의 탐지방법은 매우 높은 수준의 성능을 나타냈다.

• Proceedings of the KAIS Fall Conference
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• 2004.06a
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• pp.155-157
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• 2004

본 논문에서는 최근의 가장 대표적인 해킹 방법인 DDoS 공격도구들을 분석하고, DDoS 공격에 대한 기존에 제시된 대응방안들을 검토하여 보다 적절한 대응을 할 수 있는 DDoS 공격 탐지 및 대응 시스템을 설계한다. 제안된 시스템은 탐지 모듈에서 탐지된 공격에 대해 관리자에게 보고하여 적절한 대응을 하고 침입으로 판정되는 패킷들에 대해서는 필터링을 실시하여 네트워크 레벨에서 필터링하고 차단할 수 있는 장점을 살릴 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.69-74
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• 2021

Internet access is also increasing as online activities increase due to the influence of Corona 19. However, network attacks are also diversifying by malicious users, and DDoS among the attacks are increasing year by year. These attacks are detected by intrusion detection systems and can be prevented at an early stage. Various data sets are used to verify intrusion detection algorithms, but in this paper, CICIDS2017, the latest traffic, is used. DDoS attack traffic was analyzed using the decision tree. In this paper, we analyzed the traffic by using the decision tree. Through the analysis, a decisive feature was found, and the accuracy of the decisive feature was confirmed by proceeding the decision tree to prove the accuracy of detection. And the contents of false positive and false negative traffic were analyzed. As a result, learning the feature and the two features showed that the accuracy was 98% and 99.8% respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2512-2531
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• 2014

We propose a new Distributed Denial of Service (DDoS) defense mechanism that protects http web servers from application-level DDoS attacks based on the two methodologies: whitelist-based admission control and busy period-based attack flow detection. The attack flow detection mechanism detects attach flows based on the symptom or stress at the server, since it is getting more difficult to identify bad flows only based on the incoming traffic patterns. The stress is measured by the time interval during which a given client makes the server busy, referred to as a client-induced server busy period (CSBP). We also need to protect the servers from a sudden surge of attack flows even before the malicious flows are identified by the attack flow detection mechanism. Thus, we use whitelist-based admission control mechanism additionally to control the load on the servers. We evaluate the performance of the proposed scheme via simulation and experiment. The simulation results show that our defense system can mitigate DDoS attacks effectively even under a large number of attack flows, on the order of thousands, and the experiment results show that our defense system deployed on a linux machine is sufficiently lightweight to handle packets arriving at a rate close to the link rate.