MQT-TZ：使用ARM TrustZone强化IoT经纪人
MQT-TZ: Hardening IoT Brokers Using ARM TrustZone
摘要：
订阅模式是一种高效的通信方案，节点之间具有很强的解耦性，特别适合于大规模部署。它可以原生地适应非常动态的设置，并用于各种现实场景，包括金融，智能城市，医疗环境或物联网传感器。由于所交换的消息的敏感性以及客户端/利益相关者/接收者的隐私要求，所提到的几个应用场景需要越来越严格的安全保证。MQTT是一种轻量级的基于主题的订阅协议，在边缘和物联网环境中很受欢迎，是目前行业和研究人员广泛采用的事实标准。然而，MQTT代理必须以明文处理数据，因此暴露了大量的攻击面。本文介绍了MQT-TZ，一个利用Arm TrustZone的安全MQTT代理，这是一个可信执行环境（TEE），即使在市场上大量可用的廉价设备（如Raspberry Pi设备）上也很常见。我们定义了一个相互TLS为基础的握手和两层加密的端到端的安全使用TEE作为可信代理。我们的完全实现的原型与微观，宏观基准，以及与现实世界的工业工作负载从MedTech用例的实验评估，突出了几个权衡使用TrustZone TEE。我们报告了在构建和评估我们的系统时学到的几个经验教训。我们将MQT-TZ作为开源发布。
英文摘要：
The publish-subscribe paradigm is an efficient communication scheme with strong decoupling between the nodes, that is especially fit for large-scale deployments. It adapts natively to very dynamic settings and it is used in a diversity of real-world scenarios, including finance, smart cities, medical environments, or IoT sensors. Several of the mentioned application scenarios require increasingly stringent security guarantees due to the sensitive nature of the exchanged messages as well as the privacy demands of the clients/stakeholders/receivers. MQTT is a lightweight topic-based publish-subscribe protocol popular in edge and IoT settings, a de-facto standard widely adopted nowadays by the industry and researchers. However, MQTT brokers must process data in clear, hence exposing a large attack surface. This paper presents MQT-TZ, a secure MQTT broker leveraging Arm TrustZone, a trusted execution environment (TEE) commonly found even on inexpensive devices largely available on the market (such as Raspberry Pi units). We define a mutual TLS-based handshake and a two-layer encryption for end-to-end security using the TEE as a trusted proxy. The experimental evaluation of our fully implemented prototype with micro-, macro-benchmarks, as well as with real-world industrial workloads from a MedTech use-case, highlights several trade-offs using TrustZone TEE. We report several lessons learned while building and evaluating our system. We release MQT-TZ as open-source.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
