• KIPS Transactions on Computer and Communication Systems
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• v.7 no.1
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• pp.19-26
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• 2018

Recently, DDoS amplification attacks using servers that provide Microsoft Active Directory information using CLDAP protocol are increasing. Because CLDAP is an open standard application that allows a wide range of directory information to be accessed and maintained in a network, the server is characterized by its openness to the Internet. This can be exploited by the Reflector server to perform an amplification attack by an attacker. In addition, this attack can be attacked with a packet that is amplified 70 times more than the conventional UDP-based flooding attack, and it can block service to small and medium sized server. Therefore, in this paper, we propose an algorithm that can reduce the DDoS amplification attack using CLDAP server and implement the corresponding CLDAP server environment virtually, and implement and demonstrate the corresponding algorithm. This provides a way to ensure the availability of the server.

• 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.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.429-437
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• 2015

DDoS attacks have been used for paralyzing popular Internet services. Especially, amplification attacks have grown dramatically in recent years. Defending against amplification attacks is challenging since the attacks usually generate extremely hugh amount of traffic and attack traffic is coming from legitimate servers, which is hard to differentiate from normal traffic. Moreover, some of protocols used by amplification attacks are widely adopted in IoT devices so that the number of servers susceptible to amplification attacks will continue to increase. This paper studies on the analysis of amplification attack mechanisms in detail and proposes defense methodologies for scenarios where attackers, abused servers or victims are in a monitoring network.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.22-30
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• 2020

With the development of information and communication technology, DDoS and DRDoS continue to become security issues, and gradually develop into advanced techniques. Recently, IT companies have been threatened with DRDoS technology, which uses protocols from normal servers to exploit as reflective servers. Reflective traffic is traffic from normal servers, making it difficult to distinguish from security equipment and amplified to a maximum of Tbps in real-life cases. In this paper, after comparing and analyzing the DNS amplification and Memcached amplification used in DRDoS attacks, a countermeasure that can reduce the effectiveness of the attack is proposed. Protocols used as reflective traffic include TCP and UDP, and NTP, DNS, and Memcached. Comparing and analyzing DNS protocols and Memcached protocols with higher response sizes of reflective traffic among the protocols used as reflective traffic, Memcached protocols amplify ±21% more than DNS protocols. The countermeasure can reduce the effectiveness of an attack by using the Memcached Protocol's memory initialization command. In future studies, various security-prone servers can be shared over security networks to predict the fundamental blocking effect.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.1-9
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• 2017

Recently, the DDoS attack using the amplifier method makes it difficult to distinguish the normal traffic from the normal server and it is difficult to detect even the attack detection. Since the SSDP protocol is a common protocol widely used in IoT devices, it is used as a DDoS amplification attack. In this paper, we analyze the reflector attack of SSDP which is one of the DDoS and suggest a technical proposal to detect and defend against the attack by managing the Mac address of each device. Also, we propose a control structure to protect the reflection attack of SSDP in Home IoT. The efficiency of the proposed system has been verified by performing an experimental attack on the virtual environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.303-311
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• 2015

DNS amplification is a new type of DDoS Attack and nowadays the attack occurs frequently. The previous studies showed the several detection ways such as the traffic analysis based on DNS queries and packet size. However, those methods have some limitations such as the uncertainty of packet size which depends on IP address type and vulnerabilities against distributed amplification attack. Therefore, we proposed a novel traffic analyzing algorithm using Success Rate and implemented the query analyzing system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.108-110
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• 2021

Since 2015, attacks using the IoT protocol have been continuously reported. Among various IoT protocols, attackers attempt DDoS attacks using SSDP(Simple Service Discovery Protocol), and as statistics of cyber shelters, Korea has about 1 million open SSDP servers. Vulnerable SSDP servers connected to the Internet can generate more than 50Gb of traffic and the risk of attack increases gradually. Until recently, distributed denial of service attacks and distributed reflective denial of service attacks have been a security issue. Accordingly, the purpose of this study is to analyze the request packet of the existing SSDP protocol to identify an amplification attack and to avoid a response when an amplification attack is suspected, thereby preventing network load due to the occurrence of a large number of response packets due to the role of traffic reflection amplification.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1670-1675
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• 2020

In this study, to provide the basis for establishing effective network based countermeasures against DRDoS(Distributed Reflection Denial of Service) attacks, we propose a new 'DRDoS attack multi-level detection method' that identifies the network based characteristics of DRDoS and applies probability and statistical techniques. The proposed method removes the limit to which normal traffic can be indiscriminately blocked by unlimited competition in network bandwidth by amplification of reflectors, which is characteristic of DRDoS. This means that by comparing 'Server to Server' and 'Outbound Session Incremental' for it, accurate DRDoS identification and detection is possible and only statistical and probabilistic thresholds are applied to traffic. Thus, network-based information security systems can take advantage of this to completely eliminate DRDoS attack frames. Therefore, it is expected that this study will contribute greatly to identifying and responding to DRDoS attacks.