• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.68-76
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• 2016

The pre-paid nation-wide interoperable transportation card, which an pay fee of bus, subway, train, and highway with just one card, released in June. 2014. It has started and operated from Seoul, Gyeonggi, and major local metropolitan area. In this paper, after starting of service, we evaluate conformance and interoperability of nation-wide interoperable transportation card system in real situation. Through this, we check the status of its technical operation. For this, we choose 6 region included Seoul, Gyeonggi which are serviced by different transport vendors and check recognition and billing result from field of transportation card terminal. As a result, we can reach that the major nation-wide interoperable transportation card operate normally and deliver CONFIG DF query command. It means nation-wide interoperable transportation card system which use only one card stably adapt the public transport system and it can make user's public transport use convenience higher through the extension of service area.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.669-677
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• 2020

As the number of Internet users exploded, attacks on the web increased. In addition, the attack patterns have been diversified to bypass existing defense techniques. Traditional web firewalls are difficult to detect attacks of unknown patterns.Therefore, the method of detecting abnormal behavior by artificial intelligence has been studied as an alternative. Specifically, attempts have been made to apply natural language processing techniques because the type of script or query being exploited consists of text. However, because there are many unknown words in scripts and queries, natural language processing requires a different approach. In this paper, we propose a new classification model which uses byte pair encoding (BPE) technology to learn the embedding vector, that is often used for web attack payloads, and uses an attention mechanism-based Bi-GRU neural network to extract a set of tokens that learn their order and importance. For major web attacks such as SQL injection, cross-site scripting, and command injection attacks, the accuracy of the proposed classification method is about 0.9990 and its accuracy outperforms the model suggested in the previous study.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.4
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• pp.46-55
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• 2009

In RFID field, when the neighboring readers try to occupy the same or adjacent channel simultaneously, there exists reader-to-reader interference; it calls reader collision. From the reader collision, the tags cannot response correctly query from the reader. Reader anti-collision schemes have been developed, and particularly, the Listen-Before-Talk(LBT) scheme is proposed to avoid reader collision in ETSI in multi channel environment. However, in ETSI, there is a drawback that the reader collision does not decreases effectively because the reader selects randomly a channel without considering the channel environment and readers try to occupy the channel concurrently. In this paper, we propose a algorithm based on LBT scheme considering multi channel environment as well as made up for the drawbacks of LBT The proposed algorithm applies random backoff, the collision avoidance mechanism. And it can reduce delay because of our proposed estimation mechanism Simulation using OPNET shows that the proposed algorithm achieves higher superiority than that of the simple algorithms in sparse and dense reader mode.