A novel matrix representation for privacy-preserving spatial trajectory prediction

Wen-Chen Hu, H. Yang, N. Kaabouch, Lei Chen
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引用次数: 2

Abstract

Location-based services (LBS), one of mobile applications, have attracted a great attention recently. This research proposes a location-based service, which predicts a spatial trajectory based on the current and previous trajectories by using a novel matrix representation. Spatial trajectory prediction can be used in a variety of purposes such as travel recommendations and traffic control and planning, but at the same time, just like most location-based services, the user privacy concern is a major issue. Without rigorous privacy protection, users would be reluctant to use the service. The proposed method is simple but effective and user privacy is rigorously preserved at the same time because the trajectory prediction is performed at the user-side. Additionally, this research is not only useful but also pedagogical because it involves a variety of topics like (i) mobile computing, (ii) mobile security, and (iii) human behavior recognition.
一种新的保护隐私的空间轨迹预测矩阵表示
基于位置的服务(LBS)作为一种移动应用,近年来引起了人们的广泛关注。本研究提出了一种基于位置的服务,该服务使用一种新颖的矩阵表示,基于当前和以前的轨迹来预测空间轨迹。空间轨迹预测可以用于各种目的,如旅行推荐、交通控制和规划,但与此同时,就像大多数基于位置的服务一样,用户隐私问题是一个主要问题。如果没有严格的隐私保护,用户将不愿意使用这项服务。该方法简单有效,同时由于轨迹预测是在用户侧进行的,因此严格保护了用户的隐私。此外,这项研究不仅有用,而且具有教学意义,因为它涉及各种主题,如(i)移动计算,(ii)移动安全,(iii)人类行为识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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