Secure self-seeding with power-up SRAM states

Konrad-Felix Krentz, C. Meinel, Hendrik Graupner
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引用次数: 4

Abstract

Generating seeds on Internet of things (IoT) devices is challenging because these devices typically lack common entropy sources, such as user interaction or hard disks. A promising replacement is to use power-up static random-access memory (SRAM) states, which are partly random due to manufacturing deviations. Thus far, there, however, seems to be no method for extracting close-to-uniformly distributed seeds from power-up SRAM states in an information-theoretically secure and practical manner. Moreover, the min-entropy of power-up SRAM states reduces with temperature, thereby rendering this entropy source vulnerable to so-called freezing attacks. In this paper, we mainly make three contributions. First, we propose a new method for extracting uniformly distributed seeds from power-up SRAM states. Unlike current methods, ours is information-theoretically secure, practical, and freezing attack-resistant rolled into one. Second, we point out a trick that enables using power-up SRAM states not only for self-seeding at boot time, but also for reseeding at runtime. Third, we compare the energy consumption of seeding an IoT device either with radio noise or power-up SRAM states. While seeding with power-up SRAM states turned out to be more energy efficient, we argue for mixing both these entropy sources.
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安全自播种与上电SRAM状态
在物联网(IoT)设备上生成种子具有挑战性,因为这些设备通常缺乏常见的熵源,例如用户交互或硬盘。一种很有希望的替代方法是使用上电静态随机存取存储器(SRAM)状态,这种状态由于制造偏差部分是随机的。然而,到目前为止,似乎还没有一种从上电的SRAM状态中提取接近均匀分布的种子的方法,在信息理论上是安全和实用的。此外,上电SRAM状态的最小熵随温度降低,从而使该熵源容易受到所谓的冻结攻击。在本文中,我们主要做了三点贡献。首先,提出了一种从上电SRAM状态中提取均匀分布种子的新方法。与目前的方法不同,我们的方法在理论上是信息安全的,实用的,并能抵抗冻结攻击。其次,我们指出了一个技巧,该技巧不仅可以在引导时使用通电SRAM状态进行自播种,还可以在运行时重新播种。第三,我们比较了播种物联网设备与无线电噪声或上电SRAM状态的能耗。虽然用上电的SRAM状态播种被证明是更节能的,但我们认为应该混合这两种熵源。
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