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Hardware accelerator for data anonymization using dynamic partial reconfiguration

机译:使用动态部分重新配置的数据匿名化硬件加速器

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Smart City is a promising infrastructure for our near future community systems. It is predicted that more and more sensor devices and computing resources will be deployed in access networks because of the Internet of Things (IoT). This movement can create a wide variety of new applications with different requirements of delay, privacy and locality. Smart community dictates less than 10ms communication as a control interval in order not to disturb the lifeline systems, such as power supply. As such, future devices should have the following attributes: low-power, low-latency, and flexibility for various applications. In this paper, we propose an energy-aware, low-latency, and flexible local device, such as gateway or coordinator, which integrates an SoC FPGA with dynamic partial reconfiguration (DPR) feature to grapple with data anonymization. The data anonymization is important to protect private information in smart community because domestic human activities can be, for example, estimated by exploiting electric power consumption data, which is known as nonintrusive load monitoring (NILM). However, anonymization operations usually require processing cost at the order of O(n2) where n denotes the number of data in a privacy processing window. In case of encapsulating privacy information in a local network, privacy preserving computation should be achieved in a local device. Hence, we have implemented four primitive operations using DPR for various anonymization purposes. The proposed system achieves 18-328 times better performance and 10-200 times lower power consumption in every primitive anonymization method than Raspberry Pi 2 Model B.
机译:智能城市是我们近期未来社区系统的有前途的基础设施。预测,由于事物的因特网(物联网),将在接入网络中部署越来越多的传感器设备和计算资源。这种运动可以创建各种新应用,具有不同的延迟,隐私和地点的要求。智能社区指示较少超过10ms的通信作为控制间隔,以免干扰诸如电源的生命线系统。因此,未来的设备应具有以下属性:低功耗,低延迟和各种应用的灵活性。在本文中,我们提出了一种能量感知,低延迟和灵活的本地设备,例如网关或协调器,其与动态部分重新配置(DPR)功能集成了SOC FPGA,以掌握数据匿名化。数据匿名化对于保护智能社区中的私人信息是重要的,因为例如,通过利用电力消耗数据估计,这被称为非流通负荷监测(NILM)。然而,匿名化操作通常需要按O(n2)的顺序处理成本,其中n表示隐私处理窗口中的数据的数量。在封装本地网络中的隐私信息的情况下,应在本地设备中实现隐私保留计算。因此,我们使用DPR实现了四种原始操作,以获取各种匿名的目的。所提出的系统在比覆盆子PI 2型B模型B中的每种原始匿名方法中的性能越来越好,较低的功耗为10-200倍。

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