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An Overview of DRAM-Based Security Primitives

机译:基于DRAM的安全原语概述

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Recent developments have increased the demand for adequate security solutions, based on primitives that cannot be easily manipulated or altered, such as hardware-based primitives. Security primitives based on Dynamic Random Access Memory (DRAM) can provide cost-efficient and practical security solutions, especially for resource-constrained devices, such as hardware used in the Internet of Things (IoT), as DRAMs are an intrinsic part of most contemporary computer systems. In this work, we present a comprehensive overview of the literature regarding DRAM-based security primitives and an extended classification of it, based on a number of different criteria. In particular, first, we demonstrate the way in which DRAMs work and present the characteristics being exploited for the implementation of security primitives. Then, we introduce the primitives that can be implemented using DRAM, namely Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs), and present the applications of each of the two types of DRAM-based security primitives. We additionally proceed to assess the security such primitives can provide, by discussing potential attacks and defences, as well as the proposed security metrics. Subsequently, we also compare these primitives to other hardware-based security primitives, noting their advantages and shortcomings, and proceed to demonstrate their potential for commercial adoption. Finally, we analyse our classification methodology, by reviewing the criteria employed in our classification and examining their significance.
机译:最近的发展增加了对基于不易操纵或更改的原语(例如基于硬件的原语)的适当安全解决方案的需求。基于动态随机存取存储器(DRAM)的安全原语可以提供经济高效且实用的安全解决方案,尤其是对于资源受限的设备(例如物联网(IoT)中使用的硬件)而言,因为DRAM是大多数现代技术的固有组成部分计算机系统。在这项工作中,我们基于许多不同的标准对基于DRAM的安全原语及其扩展分类进行了全面的文献综述。特别是,首先,我们演示DRAM的工作方式,并介绍用于实现安全原语的特征。然后,我们介绍可以使用DRAM实现的原语,即物理不可克隆函数(PUF)和真实随机数生成器(TRNG),并介绍两种基于DRAM的安全原语中每种类型的应用。此外,我们还将通过讨论潜在的攻击和防御以及建议的安全度量来评估此类原语可以提供的安全性。随后,我们还将这些原语与其他基于硬件的安全原语进行比较,指出它们的优点和缺点,并继续展示其在商业上的应用潜力。最后,我们通过审查分类中使用的标准并检查其重要性来分析分类方法。

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