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Secure Opportunistic Contextual Logging for Wearable Healthcare Sensing Devices

机译:可穿戴医疗感应设备的安全机会主义的上下文测井

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Wearable technology is increasingly being used for medical applications such as continuous monitoring of chronically ill patients in homes and hospitals. The various stakeholders (patients, doctors, insurers) have an interest in ensuring not only that the data is untampered, but also that the context is verifiable (e.g., correct time and location can be associated with the data collected). Prior works have studied these aspects in isolation, typically using cryptographic techniques. In this paper, we develop a new solution that leverages the density of wireless devices in the vicinity of the transaction to create witness records ensuring data is tamper-protected and bound to its time and location context. Our first contribution is to develop a secure logging architecture that compacts witness records using Bloom filters and hash-chains them to bind them to the data, allowing fast and reliable forensic verification. Our second contribution is to identify the various configuration parameters influencing the performance of our scheme in terms of storage, processing, and transmission efficiency, and to quantify their effect on verification accuracy. Our third contribution implements and demonstrates the feasibility of our scheme, and quantifies its efficacy via simulation using real trace data from a multi-storey building representing a hospital environment.
机译:可穿戴技术越来越多地用于医疗应用,例如在家庭和医院的慢性病患者的连续监测。各种利益攸关方(患者,医生,保险公司)对不仅确保数据不足,而且还有兴趣确保上下文是可验证的(例如,正确的时间和位置可以与收集的数据相关联)。先前作品已经在隔离中研究了这些方面,通常使用加密技术。在本文中,我们开发了一种新的解决方案,它利用交易附近的无线设备密度来创建证人记录,确保数据被篡改保护并绑定到其时间和位置上下文。我们的第一个贡献是开发一个安全的日志记录架构,该架构紧致了使用绽放过滤器和哈希链绑定到数据的证人记录,允许快速可靠的法医验证。我们的第二款贡献是在存储,处理和传输效率方面识别影响我们方案性能的各种配置参数,并量化其对验证精度的影响。我们的第三种贡献实施并展示了我们方案的可行性,并通过使用代表医院环境的多层建筑物的真实跟踪数据来量化其功效。

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