互联世界中的硬件安全

Durba Chatterjee, Shuvodip Maitra, Nimish Mishra, Shubhi Shukla, Debdeep Mukhopadhyay
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引用次数: 0

摘要

物联网(IoT)的快速发展使数十亿智能设备融入我们的日常生活,产生和交换大量关键数据。虽然这种连接提供了显著的好处,但它也引入了许多安全漏洞。解决这些漏洞需要一种全面的硬件安全方法,一种评估各种攻击的相互作用和对策以保护这些系统的方法。本文提供了硬件安全策略的广泛概述,并探讨了威胁连接系统的当代攻击。我们首先介绍了针对嵌入式系统的最先进的侧信道和故障攻击,强调了广泛的物联网目标,如智能家居设备、医疗植入物、工业控制系统和汽车部件。接下来,我们将研究基于硬件的安全原语,如物理不可克隆功能(puf)和物理相关功能(pref),它们已成为在轻量级资源受限设备中建立硬件信任根的有希望的解决方案。这些原语为加密密钥的安全存储提供了强大的替代方案,对于保护各种物联网设备至关重要。此外,我们还讨论了可信架构、硬件木马和物理保证机制,强调了它们在增强不同物联网环境安全性方面的作用。最后,我们探讨了机器学习辅助攻击的范围,这些攻击在上述所有安全领域都提出了新的和有趣的挑战。本文旨在为硬件安全研究的当前挑战和未来方向提供有价值的见解,特别是与物联网设备的变化和扩展有关。本文分类如下:技术>;物联网技术;机器学习商业、法律和伦理问题安全及私隐
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hardware Security in the Connected World
The rapid proliferation of the Internet of Things (IoT) has integrated billions of smart devices into our daily lives, generating and exchanging vast amounts of critical data. While this connectivity offers significant benefits, it also introduces numerous security vulnerabilities. Addressing these vulnerabilities requires a comprehensive approach to hardware security, one that evaluates the interplay of various attacks and countermeasures to protect these systems. This article provides an extensive overview of hardware security strategies and explores contemporary attacks threatening connected systems. We begin by presenting state‐of‐the‐art side‐channel and fault attacks targeting embedded systems, emphasizing the wide range of IoT targets such as smart home devices, medical implants, industrial control systems, and automotive components. Next, we examine hardware‐based security primitives such as physically unclonable functions (PUFs) and physically related functions (PReFs), which have emerged as promising solutions for establishing a hardware root‐of‐trust in lightweight, resource‐constrained devices. These primitives provide robust alternatives to secure storage of cryptographic keys, essential for protecting the diverse array of IoT devices. Further, we discuss trusted architectures, hardware Trojans, and physical assurance mechanisms, highlighting their roles in enhancing security across different IoT environments. We conclude by exploring the expanse of machine learning‐assisted attacks, which present new and intriguing challenges across all the aforementioned security domains. This article aims to offer valuable insights into the current challenges and future directions of research in hardware security, particularly pertaining to the varied and expanding landscape of IoT devices.This article is categorized under: Technologies > Internet of Things Technologies > Machine Learning Commercial, Legal, and Ethical Issues > Security and Privacy
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