• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8C
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• pp.741-747
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• 2002

In this paper, we present a new form of DDOS attack and a mechanism to defend systems from it. Up to now the ultimate target of a DDOS attack is a specific host. But in the near future router attacks are expected to appear. Because these kinds of attacks may involve many hosts in the managed domain of a specific router, they will be still more serious than the current DDOS attacks. Also, we present an algorithm to defend against an attack on a router using survivability of the router. By using a survivability of a router, the router can control a quantity of traffic autonomously without an interruption of services even when a DDOS attack occurs.

• Journal of the Korea Convergence Society
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• v.3 no.4
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• pp.1-5
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• 2012

The fast-paced development in the field of U-Healthcare, which is available anytime and anywhere, is being underway in accordance with the development of IT technology. U-Healthcare technology has various security threats because it is based on network. The purpose of this paper is to examine the threats of DOS / DDOS attacks based on network attacks, and to propose the response technique that fit the situation of the U-Healthcare service by modifying the existing Detecting Early DOS / DDOS attacks through Packet Counting.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.565-567
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• 2002

DDOS공격은 최근 인터넷 환경에서 큰 위험요소로 부각되고 있다. 하지만, DDOS공격을 완벽하게 막아내는 것은 현재까지 알려진 방법으로는 거의 불가능하다. 그 이유는DDOS 공격이 Vulnerability Exploit을 이용한 공격방법이 아니라 Network Resource를 고갈시켜서 공격대상 호스트의 서비스를 차단하기 때문이다. 그래서, DDOS공격을 방어하기 위해서는 DDOS공격 트래픽에 대한 정확한 분석과 탐지가 선행되어야 한다. 본 논문을 통해서 여러 가지 DDOS공격 Traffic의 특징을 살펴보고, Web traffic과의 차이를 통해 DDOS traffic을 탐지하는 방법을 제안하고자 한다.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.268-272
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• 2004

Recently most of hacking attack are either DDos attack or worm attack. However detection algorithms against those attacks are insufficient. In this paper, we propose a method which is able to detect attack traffic very efficiently by reducing traffic overhead. In this scheme, network traffics are collected using SNMP and classified. if they are identified as normal traffic, traffic analysis delay timer is started to reduce traffic overhead.

• Journal of Convergence Society for SMB
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• v.5 no.1
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• pp.19-23
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• 2015

Distributed Denial of Service attack is a form of denial of service attacks, the attacker to attack a place in a number of points of attack by a wide variety of forms over the network to perform a service on a point attack . Do not use a specific server or client attempts to make a connection to many services available that prevents this attack and so normally used . Corresponding methods of DDoS attacks has a corresponding managerial aspects and technical aspects of the proposed two.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.55-65
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• 2016

Distributed Denial of service attack is one of the major threats nowadays especially to the government infrastructure that give huge impact to the reputation and interrupt the services and resource. Our survey start with brief introduction about DDoS attacks, we illustrate the trends and incident happened at government from various countries. We then provide an extensive literature review on the existing research about implication, types of attacks and initiative to defence against the DDoS attacks. Our discussion aims to identify the trends in DDoS attacks, in depth impact of DDoS attacks to government infrastructure, classification of attacks and techniques against the attacks. And we will use for a fire fight safety and management.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.772-779
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• 2012

In the current MANET, DOS or DDOS attacks are increasing, but as MANET has limited bandwidth, computational resources and battery power, the existing traceback mechanisms can not be applied to it. Therefore, in case of traceback techniques being applied to MANET, the resource of each node must be used efficiently. However, in the traceback techniques applied to an existing ad hoc network, as a cluster head which represents all nodes in the cluster area manages the traceback, the overhead of the cluster head shortens each node's life. In addition, in case of multi-hop clustering, as one Cluster head manages more node than one, its problem is getting even worse. This paper proposes TNA(Traceback against Network Attacks) based on multihop clustering using the depth of tree structure in order to reduce the overhead of distributed information management.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.170-178
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• 2024

Through the growth of the fifth-generation networks and artificial intelligence technologies, new threats and challenges have appeared to wireless communication system, especially in cybersecurity. And IoT networks are gradually attractive stages for introduction of DDoS attacks due to integral frailer security and resource-constrained nature of IoT devices. This paper emphases on detecting DDoS attack in wireless networks by categorizing inward network packets on the transport layer as either "abnormal" or "normal" using the integration of machine learning algorithms knowledge-based system. In this paper, deep learning algorithms and CNN were autonomously trained for mitigating DDoS attacks. This paper lays importance on misuse based DDOS attacks which comprise TCP SYN-Flood and ICMP flood. The researcher uses CICIDS2017 and NSL-KDD dataset in training and testing the algorithms (model) while the experimentation phase. accuracy score is used to measure the classification performance of the four algorithms. the results display that the 99.93 performance is recorded.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.8
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• pp.891-900
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• 2015

Cloud Computing has recently begun to emerge as a new attack target. The malice DDoS attacks are ongoing to delay and disturb the various services of the Cloud Computing. In this paper, we propose the Hornet-Cloud using security Honeypot technique and resources of Cloud Computing, and design the concept of active-interaction and security functions of Hornet-Cloud simply.