• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.504-509
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• 2019

Recently, both wireless communications technology and the performance of small devices have developed exponentially, while the number of services using various types of Internet of Things (IoT) devices has also massively increased in line with the ongoing technological and environmental changes. Furthermore, ever more devices that were previously used in the offline environment-including small-size sensors and CCTV-are being connected to the Internet due to the huge increase in IoT services. However, many IoT devices are not equipped with security functions, and use vulnerable open source software as it is. In addition, conventional network equipment, such as switches and gateways, operates with vulnerabilities, because users tend not to update the equipment on a regular basis. Recently, the simple vulnerability of IoT devices has been exploited through the distributed denial of service (DDoS) from attackers creating a large number of botnets. This paper proposes a system that is capable of identifying Internet-connected devices quickly, analyzing and managing the vulnerability of such devices using Internet-wide scan technology. In addition, the vulnerability analysis rate of the proposed technology was verified through collected banner information. In the future, the company plans to automate and upgrade the proposed system so that it can be used as a technology to prevent cyber attacks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.76-82
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• 2019

The development of Internet technology and the deployment of smart devices provide a convenient environment for people, and this is becoming common with the technology called the Internet of Things (IoT). But the development of, and demand for, IoT technology is causing various problems, such as personal information leaks due to the attacks of hackers who exploit it. A number of devices are connected to a network, and network attacks that have been exploited in the existing PC environment are occurring in the IoT environment. When it comes to IP cameras, security incidents (such as distributed denial of service [DDoS] attacks, hacking someone's personal information, and monitoring without consent) are occurring. However, it is difficult to install and implement existing security solutions because memory space and power are limited owing to the characteristics of small devices in the IoT environment. Therefore, this paper proposes a security protocol that can look at and prevent IoT security threats. A security assessment verified that the proposed protocol is able to respond to various security threats that could arise in a network. Therefore, it is expected that efficient operation of this protocol will be possible if it is applied to the IoT environment.

• 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.