• Title/Summary/Keyword: 거리 기반 클로킹 기법

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Road Network Distance based User Privacy Protection Scheme in Location-based Services (위치 기반 서비스에서 도로 네트워크의 거리 정보를 이용한 사용자 정보 은닉 기법)

  • Kim, Hyeong Il;Shin, Young Sung;Chang, Jae Woo
    • Spatial Information Research
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    • v.20 no.5
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    • pp.57-66
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    • 2012
  • Recent development in wireless communication technology like GPS as well as mobile equipments like PDA and cellular phone makes location-based services (LBSs) popular. However, because users request a query to LBS servers by using their exact locations while moving on the road network, users' privacy may not be protected in the LBSs. Therefore, a mechanism for users' privacy protection is required for the safe and comfortable use of LBSs by mobile users. For this, we, in this paper, propose a road network distance based cloaking scheme supporting user privacy protection in location-based services. The proposed scheme creates a cloaking area by considering road network distance, in order to support the efficient and safe LBSs on the road network. Finally, we show from our performance analysis that our cloaking scheme outperforms the existing cloaking scheme in terms of cloaking area and service time.

Efficient dummy generation for protecting location privacy in location based services (위치기반 서비스에서 위치 프라이버시를 보호하기 위한 효율적인 더미 생성)

  • Cai, Tian-yuan;Youn, Ji-hye;Song, Doo-hee;Park, Kwang-jin
    • Journal of Internet Computing and Services
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    • v.18 no.5
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    • pp.23-30
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    • 2017
  • For enjoying the convenience provided by location based services, the user needs to submit his or her location and query to the LBS server. So there is a probability that the untrusted LBS server may expose the user's id and location etc. To protect user's privacy so many approaches have been proposed in the literature. Recently, the approaches about using dummy are getting popular. However, there are a number of things to consider if we want to generate a dummy. For example, when generating a dummy, we have to take the obstacle and the distance between dummies into account so that we can improve the privacy level. Thus, in this paper we proposed an efficient dummy generation algorithm to achieve k-anonymity and protect user's privacy in LBS. Evaluation results show that the algorithm can significantly improve the privacy level when it was compared with others.