Approaches to Secure Inference in the Internet of Things: Performance Bounds, Algorithms, and Effective Attacks on IoT Sensor Networks
Approaches to Secure Inference in the Internet of Things: Performance Bounds, Algorithms, and Effective Attacks on IoT Sensor Networks
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DOI：
10.1109/msp.2018.2842261
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发表时间：
2018-09
影响因子：
14.9
通讯作者：
Jiangfan Zhang;Rick S. Blum;H. Poor
中科院分区：
文献类型：
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作者：
Jiangfan Zhang;Rick S. Blum;H. Poor
物联网（IoT）借助现代数字通信、信号处理以及大量传感器的部署，提高了普适感知和控制能力，但也带来了严峻的安全挑战。攻击者可以修改进入物联网传感器或从传感器传出的数据，这会对任何使用这些数据进行推断的算法产生严重影响。本文描述了在描述传感器数据在受攻击前如何依赖参数的任何假定统计模型下，如何针对从受攻击的数据和通信中估计参数的最佳无偏算法的性能提供严格界限（在有足够数据的情况下）。无论采用何种无偏估计算法，结果都成立，这些算法可以采用深度学习、机器学习、统计信号处理或任何其他方法。文中还举例说明了性能接近这些界限的算法。同时也描述了使受攻击数据无法用于缩小这些界限的攻击。这些攻击在界限方面提供了有保证的攻击性能，无论无偏估计系统采用何种算法。文中提供了参考文献，对本文呈现的所有具体结果进行了各种扩展，并简要讨论了低复杂度加密和物理层安全。
The Internet of Things (IoT) improves pervasive sensing and control capabilities via the aid of modern digital communication, signal processing, and massive deployment of sensors but presents severe security challenges. Attackers can modify the data entering or communicated from the IoT sensors, which can have a serious impact on any algorithm using these data for inference. This article describes how to provide tight bounds (with sufficient data) on the performance of the best unbiased algorithms estimating a parameter from the attacked data and communications under any assumed statistical model describing how the sensor data depends on the parameter before attack. The results hold regardless of the unbiased estimation algorithm adopted, which could employ deep learning, machine learning, statistical signal processing, or any other approach. Example algorithms that achieve performance close to these bounds are illustrated. Attacks that make the attacked data useless for reducing these bounds are also described. These attacks provide a guaranteed attack performance in terms of the bounds regardless of the algorithms the unbiased estimation system employs. References are supplied that provide various extensions to all of the specific results presented in this article and a brief discussion of low-complexity encryption and physical layer security is provided.