• Title/Summary/Keyword: Cloaking Region Generation Algorithm

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An Algorithm for generating Cloaking Region Using Grids for Privacy Protection in Location-Based Services (위치기반 서비스에서 개인 정보 보호를 위한 그리드를 이용한 Cloaking 영역 생성 알고리즘)

  • Um, Jung-Ho;Kim, Ji-Hee;Chang, Jae-Woo
    • Journal of Korea Spatial Information System Society
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    • v.11 no.2
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    • pp.151-161
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    • 2009
  • In Location-Based Services (LBSs), users requesting a location-based query send their exact location to a database server and thus the location information of the users can be misused by adversaries. Therefore, a privacy protection method is required for using LBS in a safe way. In this paper, we propose a new cloaking region generation algorithm using grids for privacy protection in LBSs. The proposed algorithm creates a m inimum cloaking region by finding L buildings and then performs K-anonymity to search K users. For this, we make use of not only a grid-based index structure, but also an efficient pruning techniques. Finally, we show from a performance analysis that our cloaking region generation algorithm outperforms the existing algorithm in term of the size of cloaking region.

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Efficient Dummy Generation for Protecting Location Privacy (개인의 위치를 보호하기 위한 효율적인 더미 생성)

  • Cai, Tian-Yuan;Song, Doo-Hee;Youn, Ji-Hye;Lee, Won-Gyu;Kim, Yong-Kab;Park, Kwang-Jin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.6
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    • pp.526-533
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    • 2016
  • The researches protecting user's location in location-based services(LBS) have received much attention. Especially k-anonymity is the most popular privacy preservation method. k-anonymization means that it selects k-1 other dummies or clients to make the cloaking region. This reduced the probability of the query issuer's location being exposed to untrusted parties to 1/k. But query's location may expose to adversary when k-1 dummies are concentrated in query's location or there is dummy in where query can not exist. Therefore, we proposed the dummy system model and algorithm taking the real environment into account to protect user's location privacy. And we proved the efficiency of our method in terms of experiment result.