Privacy protection has recently attracted increasingly attention in location-based services (LBS) with the development of wireless communication and mobile positioning technology. Many location-based cloaking algorithms are proposed to protect location privacy of mobile users. However, there is a scenario where the anonymous server only utilizes users defined as current users in our algorithm, who are requiring LBS requests at the current time, to form the cloaking region. If there are not enough current users at the current time, the generated cloaking region will be larger than expected. To solve this problem, we propose the probability-base location prediction ( PLP ) algorithm. Mobile users are divided into current users and historical users. According to predicting probability, historical users are also utilized to generate the cloaking region when current users are not enough to achieve the k-anonymity model. Experimental results show that PLP can predict the cloaking region as high as 90% and the cloaking region can also decrease remarkably.


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    Titel :

    Probability-Based Location Prediction Algorithm


    Beteiligte:
    Yan, Yushuang (Autor:in) / Pei, Qingqi (Autor:in) / Wang, Xiang (Autor:in) / Wang, Yong (Autor:in)


    Erscheinungsdatum :

    2017-09-01


    Format / Umfang :

    289701 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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