• Proceedings of the KAIS Fall Conference
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• 2010.05a
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• pp.214-217
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• 2010

DDoS(distributed denial of service)공격은 1990년 중반에 처음 나타나기 시작하여 1,2세대 네트워크 자체에 대한 트래픽 폭주형태의 공격에서부터 3세대 봇넷을 이용하여 특정 서버와 특정서비스를 마비시키기 위한 공격을 거쳐 4세대의 분산 형식의 C&C를 이용하는 공격의 유형으로 발전 하고 있다. DDoS공격은 점점 지능화 되고 있으며 기존의 IDS(Intrusion Detection System) 시스템을 이용한 탐지방법으로 공격을 탐지하기에는 어려움이 존재한다. 본 논문은 IDS시스템을 보다 더 지능화시키기 위한 논문으로 IDS는 내부시스템으로부터 쿼리를 넘겨받아 업데이트를 수행하고 업데이트를 수행함과 동시에 라우터에게 C&C서버로부터 나오는 패킷을 차단하도록 알려 준다. 즉, IDS에서 일어나는 False Negative문제를 줄여줌으로써 DDoS 공격에 대하여 Zombie시스템을 생성하지 못하도록 하고자 하는데 그 목적이 있으며 점점 지능화되어 가고 있는 DDoS공격에 대하여 차단을 하고자 하는 방향성을 제시하고 있다.

• The KIPS Transactions:PartC
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• v.18C no.3
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• pp.127-134
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• 2011

Malicious botnet has been used for more malicious activities, such as DDoS attacks, sending spam messages, steal personal information, etc. To prevent this, many studies have been preceded. But malicious botnets have evolved and evaded detection systems. In particular, HTTP GET Request attack that exploits the vulnerability of the application layer is used. ALAB of ALADDIN proposed by ETRI is DDoS attack detection system that HTTP GET, Incomplete GET request flooding attack detection algorithm is applied. In this paper, we extend Incomplete GET detection algorithm of ALAB and derive the optimal configuration parameters to verify the validity of the algorithm ALAB by the study of the normal and attack packets.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.81-87
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• 2020

Recently, the network configuration is being rapidly changed to enable easy and free network service configuration based on SDN/NFV. Despite the many advantages and applications of SDN, many security issues such as Distributed Denial of Service (DDoS) attacks are being constantly raised as research issues. In particular, the effectiveness of DDoS attacks is much faster, SDN is causing more and more fatal damage. In this paper, we propose an entropy-based technique to detect and mitigate DDoS attacks in SDN, and prove it through experiments. The proposed scheme is designed to mitigate these attacks by detecting DDoS attacks on single and multiple victim systems and using time - specific techniques. We confirmed the effectiveness of the proposed scheme to reduce packet loss rate by 20(19.86)% while generating 3.21% network congestion.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.283-285
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• 2012

2009년 7.7 DDoS 공격을 기점으로 DDOS 공격에 HTTP-GET 프로토콜이 공격에 주로 사용되고 있다. 본 논문에서는 클라이언트에서 개인사용자의 웹 브라우징 패턴을 분석함으로써 HTTP-GET 공격을 탐지하는 방법을 제안한다. 웹 브라우징 패턴 분석에는 Markov Model을 사용하여 사용자의 정상적인 행동패턴을 계산하고, 공격을 탐지하는데 사용한다. 제안한 방법은 클라이언트에서 개인사용자에 대한 개별적인 웹 브라우징 패턴을 분석하기 때문에 서버에서보다 계산량이 적으며, 클라이언트 레벨에서 DDoS 공격을 조기에 탐지/차단함으로써 서버에서의 DDoS 공격 탐지에 의한 부하를 줄일 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2B
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• pp.90-99
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• 2007

It might be more efficient that detections of distributed denial of service (DDoS) attacks are done in backbone domain than in individual local networks or links. However, because existing schemes for detecting DDoS attack symptoms have been focused on individual packets or flows, they require much higher computational complexities. In this paper, we propose an efficient method to detect DDoS attack symptoms in backbone networks. Unlike conventional schemes focused on individual packets or flows, the proposed method is carried at aggregate traffic level. So, our proposed schemes can be operated with very lower computational complexity, and can be run in very high-speed backbone networks.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.279-290
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• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.

• The KIPS Transactions:PartC
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• v.16C no.1
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• pp.13-20
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• 2009

Recently, as traffic flooding attacks such as DoS/DDoS and Internet Worm have posed devastating threats to network services, rapid detection and proper response mechanisms are the major concern for secure and reliable network services. However, most of the current Intrusion Detection Systems (IDSs) focus on detail analysis of packet data, which results in late detection and a high system burden to cope with high-speed network traffic. In this paper we propose an SNMP-based lightweight and fast detection algorithm for traffic flooding attacks, which minimizes the processing and network overhead of the detection system, minimizes the detection time, and provides high detection rate. The attack detection algorithm consists of three consecutive stages. The first stage determines the detection timing using the update interval of SNMP MIB. The second stage analyzes attack symptoms based on correlations of MIB data. The third stage determines whether an attack occurs or not and figure out the attack type in case of attack.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.157-165
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• 2024

The evolution of the Distributed Denial of Service Attack(DDoS Attack) method has increased the difficulty in the detection process. One of the solutions to overcome the problems caused by the limitations of the existing victim-side detection method was the source-side detection technique. However, there was a problem of performance degradation due to network traffic irregularities. In order to solve this problem, research has been conducted to detect attacks using a collaborative network between several nodes based on artificial intelligence. Existing methods have shown limitations, especially in nonlinear traffic environments with high Burstness and jitter. To overcome this problem, this paper presents a collaborative source-side DDoS attack detection technique introduced with an attention mechanism. The proposed method aggregates detection results from multiple sources and assigns weights to each region, and through this, it is possible to effectively detect overall attacks and attacks in specific few areas. In particular, it shows a high detection rate with a low false positive of about 6% and a high detection rate of up to 4.3% in a nonlinear traffic dataset, and it can also confirm improvement in attack detection problems in a small number of regions compared to methods that showed limitations in the existing nonlinear traffic environment.

• Journal of Digital Contents Society
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• v.11 no.1
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• pp.79-89
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• 2010

The government and companies build a DDoS correspondence system hastily to protect assets from cyber threats. It has become more and more intelligent and advanced such as DDoS attack. However, when outbreaks of the social incidents such as 7.7 DDoS attack(2009.7.7) or cases of the direct damage occurred, information security systems(ISS) only become the issue in the short term. As usual, sustained investment about ISS is a negative recognition. Since the characteristic of ISS is hard to recognize the effectiveness of them before incidents occurs. Also, results of incidents occurred classify attack and detection. Detailed and objective measurement criterion to measure effectiveness and efficiency of ISS is not existed. Recently, it is progress that evaluation and certification about for the information security management system(ISMS). Since these works propose only a general guideline, it is difficult to utilize as a result of ISMS improvement for organization. Therefore, this paper proposes a framework to develop main criteria by a correspondence strategy and process. It is able to detailed and objective measurements.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.2041-2044
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• 2003

네트워크에서 발생하는 다양한 침입 중에서 서비스거부공격(DoS Attack. Denial-of-Service Attack)이란 공격자가 침입대상 시스템의 시스템 자원과 네트워크 자원을 악의적인 목적으로 소모시키기 위하여 대량의 패킷을 보냄으로써 정상 사용자로 하여금 시스템이 제공하는 서비스를 이용하지 못하도록 하는 공격을 의미한다. 기존 연구에서는 시스템과 네트워크가 수신한 패킷을 분석한 후 네트워크 세션정보를 생성하여 DoS 공격을 탐지하였다. 그러나 이 기법은 공격자가 분산서비스거부공격(DDoS Attack: Distributed DoS Attack)을 하게 되면 분산된 세션정보가 생성되기 때문에 침입을 실시간으로 탐지하기에는 부적절하다. 본 논문에서는 시스템이 가지고 있는 자윈 중에서 DDoS 공격을 밭을 때 가장 민감하게 반응하는 시스템 자원을 모니터링 함으로써 DDoS 공격을 실시간으로 탐지할 수 있는 모델을 제안한다 제안 모델은 시스템이 네트워크에서 수신한 패킷을 처리하는 과정에서 소모되는 커널 메모리 소비량을 감사자료로 이용한 네트워치기반 비정상행위탐지(networked-based anomaly detection)모델이다.