Neuromorphic-Enabled Security for IoT
Neuromorphic-Enabled Security for IoT
复制标题
神经拟态物联网安全
DOI：
10.1109/newcas52662.2022.9842256
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
H. Homayoun
中科院分区：
文献类型：
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作者：
Soheil Salehi;T. Sheaves;Kevin Immanuel Gubbi;Sayed Arash Beheshti;Sai Manoj Pudukotai Dinakarrao;S. Rafatirad;Avesta Sasan;T. Mohsenin;H. Homayoun
针对资源受限的物联网设备的硬件攻击正在迅速演变。由于物联网设备在人类健康、公共交通、自动驾驶汽车、国防和环境监测等应用中的使用增加，这些威胁已成为一个重大问题。最近的研究表明，通过监控硬件功能和旁路信息，使用深度学习来窃取用户数据的潜力。此外，机器学习(ML)方法最近在物联网应用中得到了广泛采用。先进的平台需要新颖的电路和架构，这些电路和架构可以在保持一致精度的同时，将ML应用的能耗提高几个数量级。利用数字、混合信号和模拟处理的神经形态计算由于能量、导线数量和面积效率已被证明是一个很有前途的候选方案。因此，人们寻求一种有效的尖端硬件方法，用于神经形态计算，以便在物联网边缘执行快速、节能和安全的监督和非监督学习。在这里，我们将讨论使用神经形态计算模块实现物联网边缘安全的挑战和潜在优势。神经形态计算和硬件安全的交集为任务关键型和隐私保护应用中的许多物联网领域提供服务。
Hardware attacks on resource-constrained IoT devices are evolving rapidly. These threats have become a significant concern due to the increase of IoT devices used in applications such as human health, public transportation, autonomous vehicles, defense, and environmental monitoring. Recent studies show the potential of using deep learning to steal user data by monitoring hardware features and side-channel information. Additionally, machine learning (ML) approaches have recently been widely adopted in IoT applications. Advanced platforms demand novel circuits and architectures that can yield several orders of magnitude improvements in energy consumption in ML applications while maintaining consistent accuracy. Neuromorphic computing leveraging digital, mixed-signal, and analog processing has been shown to be a promising candidate due to energy, wire count, and area efficiency. Thus, an effective cutting-edge hardware approach for neuromorphic computing to perform rapid, energy-efficient, and secure supervised and unsupervised learning at the IoT edge is sought. Here we discuss the challenges and potential benefits of using neuromorphic computing modules for security at the IoT edge. The intersection of neuromorphic computing and hardware security serves many IoT domains in mission-critical and privacy-preserving applications.