SenseHash: Computing on Sensor Values Mystified at the Origin
SenseHash: Computing on Sensor Values Mystified at the Origin
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DOI：
10.1109/tetc.2022.3217488
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发表时间：
2024-04
影响因子：
5.9
通讯作者：
Nojan Sheybani;Xinqiao Zhang;S. Hussain;F. Koushanfar
中科院分区：
文献类型：
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作者：
Nojan Sheybani;Xinqiao Zhang;S. Hussain;F. Koushanfar
我们提出了SenseHash，一种新颖的设计，用于在原点对感测数据进行轻量级的硬件神秘化。该框架旨在确保敏感传感器值的隐私，同时保留其实用性。传感器被假定为与物联网（IoT）和其他新兴普适计算场景中的各种（潜在恶意）通信和计算组件进行接口。我们的工作的主要安全原语是局部敏感哈希（LSH）结合差分隐私（DP）和LSH的安全构造。我们的构造允许（i）在传感器读数中进行次线性搜索，同时确保其免受三角测量攻击的安全性，以及（ii）读数的差分私有统计。SenseHash包括硬件架构以及附带的协议，以有效地利用实际场景中的安全读数。除了这些情况下，我们提出了一个自动化的工作流程来概括神秘化的读数的应用。FPGA实现的概念验证系统证明了其实用性和低开销的硬件资源，能源消耗，和协议执行时间。
We propose SenseHash, a novel design for the lightweight in-hardware mystification of the sensed data at the origin. The framework aims to ensure the privacy of sensitive sensor values while preserving their utility. The sensors are assumed to interface to various (potentially malicious) communication and computing components in the Internet-of-things (IoT) and other emerging pervasive computing scenarios. The primary security primitives of our work are Locality Sensitive Hashing (LSH) combined with Differential Privacy (DP) and secure construction of LSH. Our construction allows (i) sub-linear search in sensor readings while ensuring their security against triangulation attack, and (ii) differentially private statistics of the readings. SenseHash includes hardware architecture as well as accompanying protocols to efficiently utilize the secure readings in practical scenarios. Alongside these scenarios, we present an automated workflow to generalize the application of the mystified readings. Proof-of-concept FPGA implementation of the system demonstrates its practicability and low overhead in terms of hardware resources, energy consumption, and protocol execution time.