高级检索
    刘强, 李桐, 于洋, 蔡志平, 周桐庆. 面向可穿戴设备的数据安全隐私保护技术综述[J]. 计算机研究与发展, 2018, 55(1): 14-29. DOI: 10.7544/issn1000-1239.2018.20160765
    引用本文: 刘强, 李桐, 于洋, 蔡志平, 周桐庆. 面向可穿戴设备的数据安全隐私保护技术综述[J]. 计算机研究与发展, 2018, 55(1): 14-29. DOI: 10.7544/issn1000-1239.2018.20160765
    Liu Qiang, Li Tong, Yu Yang, Cai Zhiping, Zhou Tongqing. Data Security and Privacy Preserving Techniques for Wearable Devices: A Survey[J]. Journal of Computer Research and Development, 2018, 55(1): 14-29. DOI: 10.7544/issn1000-1239.2018.20160765
    Citation: Liu Qiang, Li Tong, Yu Yang, Cai Zhiping, Zhou Tongqing. Data Security and Privacy Preserving Techniques for Wearable Devices: A Survey[J]. Journal of Computer Research and Development, 2018, 55(1): 14-29. DOI: 10.7544/issn1000-1239.2018.20160765

    面向可穿戴设备的数据安全隐私保护技术综述

    Data Security and Privacy Preserving Techniques for Wearable Devices: A Survey

    • 摘要: 基于可穿戴设备的移动计算被视为支撑泛在感知型应用的重要技术,它使用大范围部署的传感器持续不断地感知环境信息,利用短距通信和数据挖掘/机器学习技术传递和处理感知数据.现有的可穿戴设备相关工作主要关注新型移动应用、信息采集、产品形态和人性化用户接口等方面的设计与实现.然而,面向可穿戴设备的数据安全隐私保护技术研究尚处于起步阶段.从数据分析者的视角来看,研究者分析可穿戴设备的数据源特点与隐私安全隐患,重点研究基于多源感知数据的个体活动识别方法和数据挖掘机制;从隐私安全保护者的视角来看,面向可穿戴设备的隐私保护技术亟需解决云辅助的隐私保护机制、隐私感知的个人信息发布和基于策略的访问控制等方面的问题.以可穿戴健康跟踪设备Fitbit为对象展开了可穿戴设备安全与隐私实例分析.最后,总结了面向可穿戴设备的隐私保护的8条技术途径,并展望了需要进一步研究的热点问题.

       

      Abstract: Mobile computing based on wearable devices is considered as the important technology for supporting ubiquitous perceptual applications. It uses widespread sensors to continuously sense the environment information. Moreover, it also adopts short-range communication and data mining/machine learning to transmit and process the sensed data, respectively. Current work mainly focuses on designing and implementing new mobile applications, information gathering, product modality and friendly user interfaces. However, research on data security and privacy technology for wearable devices is still in its fancy. In the perspective of data analysts, researchers analyze the characteristics of diverse data in wearable devices and privacy threats targeting wearable devices. Moreover, they are particularly interested in human activity recognition techniques and data mining mechanisms based on multi-source sensing data. On the other hand, it is vital for privacy protectors of wearable devices to study on privacy preservation techniques in the following three aspects: cloud-assisted privacy preserving mechanisms, privacy-aware personal data publishing and policy-based access control. A case study regarding security and privacy for Fitbit, a kind of wearable devices for health tracking, is presented. At last, the technological approaches to preserve data security and privacy for wearable devices are summarized, and some open issues to be further studied are also raised.

       

    /

    返回文章
    返回