• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.551-558
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• 2015

As more people use Wi-Fi and hotspot, unauthorized APs become one of big security problems in modern society. From the beginning of 2010, researchers study about unauthorized AP continually and contributed a lot of methods of detecting unauthorized AP that use wireless resources. Many researches about unauthorized AP detection use time-delay measurement (e.g., average or standard deviation) which is caused by additional wireless connection. In the most previous researches, however, the unauthorized APs consist of laptop and pulg-in Wi-Fi adaptor, and researchers did not concern about time-delay caused by software network sharing. In this paper, we show that existing unauthorized AP detection scheme that can not efficiently classify the high performance unauthorized AP.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.11-18
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• 2016

Accessing unauthorized rogue APs in WiFi environments is a very dangerous behavior which may lead WiFi users to be exposed to the various cyber attacks such as sniffing, phishing, and pharming attacks. Therefore, prompt and precise detection of rogue APs and properly alarming to the corresponding users has become one of most essential requirements for the WiFi security. This paper proposes a new rogue AP detection method which is mainly using the installation information of authorized APs and the DHCP snooping information of the corresponding switches. The proposed method detects rogue APs promptly and precisely, and notify in realtime to the corresponding users. Since the proposed method is simple and does not require any special devices, it is very cost-effective comparing to the wireless intrusion prevention systems which are normally based on a number of detection sensors and servers. And it is highly precise and prompt in rogue AP detection and flexible in deployment comparing to the existing rogue AP detection methods based on the timing information, location information, and white list information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.363-364
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• 2015

On the area which is restricted an unauthorized WiFi service, mobile WiFi hotspot causes security problems like leaking and gathering internal data. In this paper, we modify a wireless lan driver and implement a detector that periodically scans the wireless channels.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.232-234
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• 2017

사이버전 피해평가에 있어서 유무선 통합 환경에 대한 공격의 탐지와 이에 대한 평가가 필요한 상황이다. 특히 회사, 정부 및 군 시설 등에서 인가되지 않은 AP를 사용하여 공격이 발생하는 경우 각종 바이러스 및 해킹 공격에 의한 피해가 발생한 가능성이 높다. 띠라서 인가된 AP와 인가되지 않은 AP를 탐지해서 찾아 내야한다. 본 논문에서는 인가된 AP와 인가 되지 않은 AP를 탐지하기 위해 RTT(Round Trip Time)값을 데이터셋으로 만들고 각 기계학습 알고리즘 SVM(Support Vector Machine), J48(C4.5), KNN(K nearest neighbors), MLP(Multilayer Perceptron)의 결과를 비교해 성능의 차이를 밝히고 이를 통하여 공격을 탐지하여 피해평가에 연결이 되도록 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.761-763
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• 2013

AP 접속을 통한 인터넷 사용시에 인가되지 않은 AP의 경우 모바일 단말로부터 무선랜 연결을 유도하여 피해자가 주고 받는 패킷 정보를 도청한다. 특히 피해자가 무선랜 자동 연결 설정을 활성화한 경우 의도하지 않게 공격에 노출 될 수 있다. 따라서 이를 보안하기 위해 연결할 AP의 내부 네트워크 정보를 비교하여 정상적인 AP 인지 구별할 수 있는 방법을 제안하고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.1012-1017
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• 2008

Recently, the use of wireless fan is increased by the development of wireless communication and convenience. Moreover, it makes an issue of security threat and vulnerability of wireless tan. Therefore, the IEEE established new standard such as 802.11i in 802.11 to supplement security vulnerability of wireless tan. But the security threat that does not solve, still remains. In this paper, we proposed that the location detection algorithm, that is used Kalman-Filter, Lateration and RSSI, and the mechanism that detects security status of AP and unauthorized AP by using beacon-frame of AP in building. Finally, we confirmed performance of proposed algorithm is good in comparison of established algorithm.