Suárez-Albela Manuel, Fernández-Caramés Tiago M, Fraga-Lamas Paula, Castedo Luis
Department Computer Engineering, Faculty of Computer Science, Universidade da Coruña, 15071 A Coruña, Spain.
Sensors (Basel). 2017 Aug 29;17(9):1978. doi: 10.3390/s17091978.
Fog computing extends cloud computing to the edge of a network enabling new Internet of Things (IoT) applications and services, which may involve critical data that require privacy and security. In an IoT fog computing system, three elements can be distinguished: IoT nodes that collect data, the cloud, and interconnected IoT gateways that exchange messages with the IoT nodes and with the cloud. This article focuses on securing IoT gateways, which are assumed to be constrained in terms of computational resources, but that are able to offload some processing from the cloud and to reduce the latency in the responses to the IoT nodes. However, it is usually taken for granted that IoT gateways have direct access to the electrical grid, which is not always the case: in mission-critical applications like natural disaster relief or environmental monitoring, it is common to deploy IoT nodes and gateways in large areas where electricity comes from solar or wind energy that charge the batteries that power every device. In this article, how to secure IoT gateway communications while minimizing power consumption is analyzed. The throughput and power consumption of Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC) are considered, since they are really popular, but have not been thoroughly analyzed when applied to IoT scenarios. Moreover, the most widespread Transport Layer Security (TLS) cipher suites use RSA as the main public key-exchange algorithm, but the key sizes needed are not practical for most IoT devices and cannot be scaled to high security levels. In contrast, ECC represents a much lighter and scalable alternative. Thus, RSA and ECC are compared for equivalent security levels, and power consumption and data throughput are measured using a testbed of IoT gateways. The measurements obtained indicate that, in the specific fog computing scenario proposed, ECC is clearly a much better alternative than RSA, obtaining energy consumption reductions of up to 50% and a data throughput that doubles RSA in most scenarios. These conclusions are then corroborated by a frame temporal analysis of Ethernet packets. In addition, current data compression algorithms are evaluated, concluding that, when dealing with the small payloads related to IoT applications, they do not pay off in terms of real data throughput and power consumption.
雾计算将云计算扩展到网络边缘，支持新的物联网（IoT）应用和服务，这些应用和服务可能涉及需要隐私和安全保护的关键数据。在物联网雾计算系统中，可以区分出三个要素：收集数据的物联网节点、云，以及与物联网节点和云交换消息的互联物联网网关。本文重点关注保护物联网网关的安全，假定这些网关在计算资源方面受到限制，但能够减轻云的一些处理负担，并减少对物联网节点响应的延迟。然而，通常认为物联网网关可以直接接入电网，但实际情况并非总是如此：在诸如自然灾害救援或环境监测等关键任务应用中，通常会在大面积区域部署物联网节点和网关，这些区域的电力来自太阳能或风能，用于为为每个设备供电的电池充电。本文分析了如何在最小化功耗的同时保护物联网网关通信的安全。考虑了Rivest-Shamir-Adleman（RSA）和椭圆曲线密码学（ECC）的吞吐量和功耗，因为它们非常流行，但在应用于物联网场景时尚未得到充分分析。此外，最广泛使用的传输层安全（TLS）密码套件使用RSA作为主要的公钥交换算法，但所需的密钥大小对大多数物联网设备来说不实用，也无法扩展到高安全级别。相比之下，ECC是一种更轻量级且可扩展的替代方案。因此，对RSA和ECC在等效安全级别下进行了比较，并使用物联网网关测试平台测量了功耗和数据吞吐量。获得的测量结果表明，在提出的特定雾计算场景中，ECC显然比RSA是更好的选择，在大多数场景中能耗降低高达50%，数据吞吐量是RSA的两倍。然后通过对以太网数据包的帧时间分析来证实这些结论。此外，对当前的数据压缩算法进行了评估，得出的结论是，在处理与物联网应用相关的小数据包时，它们在实际数据吞吐量和功耗方面并无益处。
