• 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 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 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.