• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.298-300
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• 2004

인터넷을 통한 보안 위협 중 대표적 방법으로는 분산 서비스 거부 공격(DDoS)이 있다. DDoS은 해킹 공격자가 공격 근원지 IP 주소를 스푸핑하여 공격목표로 하는 시스템의 가용자원을 고갈시키거나 과도한 부하를 유발시켜 서비스를 중단시킨다. 이에 대한 대응 기술로 제시된 IP 역추적 기술은 DDoS 공격의 근원지를 판별하고 공격 패킷이 네트워크 상에서 전달된 경로를 재구성하는 기법이다. 본 연구에서는 기존의 역추적 기술인 패킷 마킹 기법에서 DDoS 공격에 대한 판별 과정 없이 임의의 패킷에 대해 역추적 정보를 생성 즉 DDoS 공격에 능동적으로 대응하고 있지 못하는 단점에 착안하여 DDoS 공격 패킷에 대해 개선된 패킷 마킹 기법을 제시하고, 또한 TTL을 통하여 스푸핑 된 IP 근원지를 효율적으로 역추적하는 방안을 제시하였으며, 실험 결과 네트워크 부하를 줄이면서도 역추적 성능을 향상시킬 수 있었다.

• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.33-38
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• 2016

DDoS attack has been continuously utilized that caused the excessively large amount of traffic that network bandwidth or server was unable to deal with paralyzing the service. Most of the people regard NTP as the biggest cause of DDoS. However, according to recently executed DDoS attack, there have been many SSDP attack in the use of amplified technique. According to characteristics of SSDP, there is no connection for making a forgery of source IP address and amplified resources feasible. Therefore, it is frequently used for attack. Especially, as it is mostly used as a protocol for causing DDoS attack on IoT devices that constitute smart home including a wireless router, media server, webcam, smart TV, and network printer. Hereupon, it is anticipated for servers of attacks to gradually increase. This might cause a serious threat to major information of human lives, major government bodies, and company system as well as on IoT devices. This study is intended to identify DDoS attack techniques in the use of weakness of SSDP protocol occurring in IoT devices and attacking scenario and counter-measures on them.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1482-1485
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• 2009

DDoS 공격은 네트워크 보안에 큰 피해를 미치는 공격기법의 하나로써, 국내외로 많은 피해를 유발하고 있으며, 최근에도 DDoS 공격에 의한 피해는 빈번하게 보고되고 있다. DDoS 공격은 실제 공격에 앞서 웜과 악성 BOT을 이용하여 공격을 직접 수행할 호스트를 감염시킨다. 웜과 악성 BOT이 타깃 호스트를 감염시키기 전에 반드시 수행하는 것이 취약점에 대한 스캐닝이다. 본 논문에서는 웜과 악성 BOT의 스캐닝 행위에 초점을 맞추어 DDoS 공격으로부터 안전한 네트워크를 구축하기 위한 역 IP spoofing을 이용한 DDoS 웜 스캐닝 트래픽의 처리기법을 제안한다.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.45-54
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• 2007

As one of the most threatening attacks, DDoS attack makes distributed multiple agents consume some critical resources at the target within the short time, thus the extent and scope of damage is serious. Against the problems, the existing defenses focus on detection, traceback (identification), and filtering. Especially, in the hierarchical networks, the traffic congestion of a specific node could incur the normal traffic congestion of overall lower nodes, and also block the control traffic for notifying the attack detection and identifying the attack agents. In this paper, we introduce a DDoS attack tolerant network structure using a hierarchical overlay for hierarchical networks, which can convey the control traffic for defense such as the notification for attack detection and identification, and detour the normal traffic before getting rid of attack agents. Lastly, we analyze the overhead of overlay construction, the possibility of speedy detection notification, and the extent of normal traffic transmission in the attack case through simulation.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.362-365
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• 2015

DDoS 공격의 빈도와 규모가 계속 증가하고 있으며 그에 따른 피해와 파급도 커지고 있다. 최근 동향에서 봇넷을 이용한 패킷 플루딩 공격이 여전히 상위 공격순위를 차지하고 있다. 공격유형으로는 TCP SYN, UDP fragment 및 SSDP 플루딩 공격 등이 여전히 강세를 보이고 있다. 이러한 공격들은 source IP가 변조된 악의적인 패킷을 대량으로 발생시켜서 공격대상 네트워크 인프라를 마비시킨다. DDoS 공격 탐지를 위해서는 내부로 유입되는 초당 패킷수와 사용자와 서버간의 연결이 네트워크 플로우수의 변화를 관측하는 것이 필요하며 방어를 위해 트래픽 제어 기술이 필요하다. 이에 본 논문에서는 네트워크 서비스 분석 및 제어 기술인 DPI/QoS 솔루션을 이용한 플로우 기반의 DDoS 탐지 및 방어 시스템을 제안한다. 네트워크 모니터링과 제어를 위하여 사용하던 DPI/QoS 솔루션에 DDoS 탐지 및 방어기능을 추가함으로써 효율성 및 경제성에서 강점을 가질 것으로 기대한다.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.135-142
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• 2017

DDoS (Distributed Denial of Service) exhausts the target server's resources using the large number of zombie pc, As a result normal users don't access to server. DDoS Attacks steadly increase by many attacker, and almost target of the attack is critical system such as IT Service Provider, Government Agency, Financial Institution. In this paper, We will introduce the CNN (Convolutional Neural Network) of deep learning based real-time detection system for DNS amplification Attack (DNS DDoS Attack). We use the dataset which is mixed with collected data in the real environment in order to overcome existing research limits that use only the data collected in the experiment environment. Also, we build a deep learning model based on Convolutional Neural Network (CNN) that is used in pattern recognition.

• 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 Security & Cryptology
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• v.20 no.5
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• pp.99-110
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• 2010

Recently, network based DDoS attacks have been changed into application layer DDoS attacks which are targeted at the web services. Specially, an attacker makes zombie PCs generate small traffic and its traffic pattern has been similar to the normal user's pattern. So, existing HTTP PPS based Threshold cannot defend the DDoS attacks effectively. In this paper, we displayed all the GET Flooding attack types and propose three DDoS attack defense mechanisms which are simple and very powerful. Proposed mechanisms can defend all the existing GET Flooding DDoS attacks and be deployed in the real environment immediately with little resource consumption.

• Journal of Internet Computing and Services
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• v.6 no.1
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• pp.13-25
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• 2005

Distributed Denial-of-Service(DDoS) attack prevent users from accessing services on the target network by spoofing its origin source address with a large volume of traffic. The objective of IP Traceback is to determine the real attack sources, as well as the full path taken by the attack packets. Existing IP Traceback methods can be categorized as proactive or reactive tracing. Existing PPM based tracing scheme(such as router node appending, sampling and edge sampling) insert traceback information in IP packet header for IP Traceback. But, these schemes did not provide enhanced performance in DDoS attack. In this paper, we propose a 'TTL based advanced Packet Marking' mechanism for IP Traceback. Proposed mechanism can detect and control DDoS traffic on router and can generate marked packet for reconstructing origin DDoS attack source, by which we can diminish network overload and enhance traceback performance.

• Convergence Security Journal
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• v.16 no.4
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• pp.17-24
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• 2016

Many companies and organizations are building a mobile office environment using the LTE network, the national disaster network and Air Force LTE network are built for public safety and national defense. However the recent threats on information security have been evolving from information leakage to DDoS attacks to neutralize the service. Especially, the type of device such as Smart phones, smart pad, tablet PC, and the numbers are growing exponentially and As performance of mobile device and speed of line develop rapidly, DDoS attacks in the mobile environment is becoming a threat. So far, universal countermeasure to DDoS attacks has been interception the network and server step, Yet problem regarding DDoS attack traffic on mobile network and expenditure of network resources still remains. Therefore, this paper analyzes the traffic type distributed in the private mobile network such as the National Disaster Network, and Air Force LTE network in order to preemptively detect DDoS attacks on terminal step. However, as direct analysis on traffic distributed in the National Disaster Network, and Air Force LTE network is restricted, transmission traffics in Minecraft and uploading video file upload which exhibit similar traffic information are analyzed in time series, thereby verifing its effectiveness through establishment of DDoS attacks standard in mobile network and application that detects and protects DDoS attacks