一种用于保护资源受限物联网设备的超轻量级白盒加密方案

Yang Shi, Wujing Wei, Zongjian He, Hongfei Fan
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引用次数: 18

摘要

无线传感器网络节点、电子标签读取器、车联网路边单元、智能手表和手环等计算资源受限的嵌入式设备在物联网中得到了广泛的应用。许多这样的设备部署在不可信的环境中,其他设备可能很容易丢失,导致可能被对手捕获。因此,在安全研究的上下文中,这些设备运行在白盒攻击环境中,攻击者可以完全看到内置密码系统的实现,并完全控制其执行。在白盒攻击环境中处理来自强大对手的攻击无疑是一个重大挑战。针对白盒攻击上下文的现有加密算法通常需要大量内存使用,从1兆到数十兆不等,因此不适合资源受限的设备。作为应对这种情况的对策,我们提出了一种超轻量级的加密方案来保护白盒攻击环境下数据的机密性。加密是使用专用于资源受限设备的秘密组件执行的,用于抵御白盒攻击,加密算法需要相对较少的静态数据,范围从48到92 KB。理论分析了该方案的安全性和效率,得到了积极的结果,实验评估表明,该方案在有限的内存使用和较低的计算成本方面满足资源约束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An ultra-lightweight white-box encryption scheme for securing resource-constrained IoT devices
Embedded devices with constrained computational resources, such as wireless sensor network nodes, electronic tag readers, roadside units in vehicular networks, and smart watches and wristbands, are widely used in the Internet of Things. Many of such devices are deployed in untrustable environments, and others may be easy to lose, leading to possible capture by adversaries. Accordingly, in the context of security research, these devices are running in the white-box attack context, where the adversary may have total visibility of the implementation of the built-in cryptosystem with full control over its execution. It is undoubtedly a significant challenge to deal with attacks from a powerful adversary in white-box attack contexts. Existing encryption algorithms for white-box attack contexts typically require large memory use, varying from one to dozens of megabytes, and thus are not suitable for resource-constrained devices. As a countermeasure in such circumstances, we propose an ultra-lightweight encryption scheme for protecting the confidentiality of data in white-box attack contexts. The encryption is executed with secret components specialized for resource-constrained devices against white-box attacks, and the encryption algorithm requires a relatively small amount of static data, ranging from 48 to 92 KB. The security and efficiency of the proposed scheme have been theoretically analyzed with positive results, and experimental evaluations have indicated that the scheme satisfies the resource constraints in terms of limited memory use and low computational cost.
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