• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5256-5262
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• 2014

Recently, Distributed Denial of Service (DDoS) attacks, such as spreading malicious code, cyber-terrorism, have occurred in government agencies, the press and the financial sector. DDoS attacks are the simplest Internet-based infringement attacks techniques that have fatal consequences. DDoS attacks have caused bandwidth consumption at the network layer. These attacks are difficult to detect defend against because the attack packets are not significantly different from normal traffic. Abnormal traffic is threatening the stability of the network. Therefore, the abnormal traffic by generating indications will need to be detected in advance. This study examined the abnormal traffic detection technique using a forecasting model-based trend model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.203-209
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• 2014

Today, Distributed denial of service (DDoS) attack present a very serious threat to the stability of the internet. The DDoS attack, which is consuming all of the computing or communication resources necessary for the service, is known very difficult to protect. The DDoS attack usually transmits heavy traffic data to networks or servers and they cannot handle the normal service requests because of running out of resources. It is very hard to prevent the DDoS attack. Therefore, an intrusion detection system on large network is need to efficient real-time detection. In this paper, we propose the detection mechanism using analysis of flow information against DDoS attacks in order to guarantee the transmission of normal traffic and prevent the flood of abnormal traffic. The OPNET simulation results show that our ideas can provide enough services in DDoS attack.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.9-16
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• 2021

Due to the prolonged infectious disease of COVID-19 worldwide, there are various security threats due to network attacks on Internet of Things devices that are vulnerable to telecommuting. Initially, users of Internet of Things devices were exploited for vulnerabilities in Remote Desktop Protocol, spear phishing and APT attacks. Since then, the technology of network attacks has gradually evolved, exploiting the simple service discovery protocol of Internet of Things devices, and DRDoS attacks have continued to increase. Existing SSDPs are accessible to unauthorized devices on the network, resulting in problems with information disclosure and amplification attacks on SSDP servers. To compensate for the problem with the authentication procedure of existing SSDPs, we propose a hash-based SSDP that encrypts server-specific information with hash and adds authentication fields to both Notify and M-Search message packets to determine whether an authorized IoT device is present.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.143-145
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• 2022

With the spread of the Internet around the world, devices connected to the Internet are gradually increasing. In addition, the number of distributed reflection service attacks (DrDoS), an attack that maliciously requests large responses by deceiving IPs as if the attacker was a victim, using vulnerabilities in application protocols such as DNS, NTP, and CLDAP, is increasing rapidly. It is believed that the security threat of distributed reflection service attacks will not disappear unless ISPs establish appropriate countermeasures to IP Spoofing. Therefore, this paper describes the security threat and response status of distributed reflection service attacks based on IP Spoofing.

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.339-350
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• 2010

Despite lots of efforts to obtain an accurate picture of structure at the level of individual ASes, there is a few application works using the AS-level Internet topology. In this paper, we show that the power-law fits the number of down-stream customer ASes very well and also present the distributions of AS links with the "public view" from UCLA IRL laboratory. Moreover, we obtain the distributions of source-destination pairs of routing hops for two sites in Korea and the United States, and then we propose a new method to decide the randomness of Internet traffic using the obtained distributions and the BGP valley-free routing policy. The randomness of traffic must be a portent of outbreak of the distributed denial-of-service attacks.

• 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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.59.1-59
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• 2001

The attackers on Internet-connected systems we are seeing today are more serious and more technically complex than those in the past. Computer security incidents are different from many other types of crimes because detection is unusually difficult. So, network security managers need a IDS and Firewall. IDS (Intrusion Detection System) monitors system activities to identify unauthorized use, misuse or abuse of computer and network system. It accomplishes these by collecting information from a variety of systems and network resources and then analyzing the information for symptoms of security problems. A Firewall is a way to restrict access between the Internet and internal network. Usually, the input ...

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.225-226
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• 2011

IP traceback is an solution for Defending against distributed denial-of-service attacks, the Fragment Marking Scheme is the famous method for IP traceback problem. In this paper, we are interested in understanding the reconstruction process at the victim of Fragment Marking Scheme deeply and make us more clearly about its limitation based on some papers mentioning it.