• 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 Internet Computing and Services
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• v.13 no.2
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• pp.41-49
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• 2012

Wireless network support and extended mobile network environment with exponential growth of smart phone users allow us to utilize the network anytime or anywhere. Malicious attacks such as distributed DOS, internet worm, e-mail virus and so on through high-speed networks increase and the number of patterns is dramatically increasing accordingly by increasing network traffic due to this internet technology development. To detect the patterns in intrusion detection systems, an existing research proposed an efficient algorithm called the jumping window algorithm and analyzed approximately 2,000 patterns in Snort 2.1.0, the most famous intrusion detection system. using the algorithm. However, it is inappropriate from the number of TCAM lookups and TCAM memory efficiency to use the result proposed in the research in current environment (Snort 2.9.0) that has longer patterns and a lot of patterns because the jumping window algorithm is affected by the number of patterns and pattern length. In this paper, we simulate the number of TCAM lookups and the required TCAM size in the jumping window with approximately 8,100 patterns from Snort-2.9.0 rules, and then analyse the simulation result. While Snort 2.1.0 requires 16-byte window and 9Mb TCAM size to show the most effective performance as proposed in the previous research, in this paper we suggest 16-byte window and 4 18Mb-TCAMs which are cascaded in Snort 2.9.0 environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.71-82
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• 2011

The RFID system provides undeniable advantages so that it is used for various application. However recent RFID system is vulnerable to some attacks as eavesdropping, replay attack, message hijacking, and tag tampering, because the messages are transmitted through the wireless channel and the tags are cheap. Above attacks cause the tag and reader impersonation, denial of service by invalidating tag, and the location tracking concerning bearer of tags, A lot of RFID authentication protocol bas been proposed to solve the vulnerability. Since Weis, Sanna, Rivest, and Engel, proposed the bash-based RFID authentication protocol, many researchers have improved hash-based authentication protocol and recent bash-based authentication protocols provide security and desirable privacy. However, it remains open problem to reduce the tag identification time as long as privacy and security are still guaranteed. Here we propose a new protocol in which the tags generate the message depending on the state of previous communitions between tag and reader. In consequence, our protocol allows a server to identify a tag in a reasonable amount of time while ensuring security and privacy, To be specific, we reduced the time for the server to identify a tag when the last session finished abnormally by at least 50% compared with other bash-based schemes that ensure levels of security and privacy similar to ours.

• 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.