Synergy: Collaborative: CPS-Security: End-to-End Security for the Internet of Things

计算无处不在。贺卡的处理器可以播放歌曲。烟花有精确定时引爆的处理器。计算机安装在发动机中，监测燃烧和性能。它们存在于我们的家中、医院、办公室、烤箱、飞机、火车和汽车中。当这些计算机联网时，将形成物联网（IoT）。由此产生的应用程序和服务具有比万维网更具变革性的潜力。安全隐患是巨大的。如今，网络威胁会窃取信用卡。明天的互联网威胁将使家庭安全系统瘫痪，洪水泛滥，并扰乱医院。根本问题是，这些应用程序由小型低功耗设备和云服务器上的软件组成，网络连接困难，收集敏感数据，这些数据需要强大的加密，但通常是由不具备这些领域专业知识的开发人员编写的。这项研究的目标是使两名开发人员能够在三个月内构建一个完整、安全的物联网应用程序。这项研究着重于四个重要原则。第一个是分布式模型视图控制器开发人员将应用程序编写为模型-视图-控制器系统的分布式管道。模型指定应用程序生成和存储的数据，而称为转换的新抽象指定数据如何从一个模型移动到另一个模型。第二种是“嵌入式网关云”。通用架构主导着物联网应用。嵌入式设备通过低功耗无线与网关通信。网关处理数据并与更广泛的互联网中的云系统通信。将分布式模型视图控制器集中在这个主要的体系结构上，充分约束了问题，使系统安全等问题变得容易处理。第三个是“端到端安全”。数据从嵌入式设备中加密出来，只能由最终用户应用程序解密。服务器可以对加密的数据进行计算，许多参与方可以在不了解输入的情况下协作计算结果。对数据处理管道的分析允许系统和运行时断言和验证整个应用程序的安全属性。最后一个原则是“软件定义硬件”。由于设计新的嵌入式设备硬件非常耗时，开发人员依赖于一般的、过度的解决方案，而忽略了由此产生的安全隐患。数据处理管道可以编译成原型硬件设计和支持软件，以及测试用例、诊断和调试方法，供开发人员启动新设备。这些原则基于Ravel，这是一个团队合作的软件框架，共同贡献，并将其集成到他们的课程和网络物理系统课程中。

Computation is everywhere. Greeting cards have processors that play songs. Fireworks have processors for precisely timing their detonation. Computers are in engines, monitoring combustion and performance. They are in our homes, hospitals, offices, ovens, planes, trains, and automobiles. These computers, when networked, will form the Internet of Things (IoT). The resulting applications and services have the potential to be even more transformative than the World Wide Web. The security implications are enormous. Internet threats today steal credit cards. Internet threats tomorrow will disable home security systems, flood fields, and disrupt hospitals. The root problem is that these applications consist of software on tiny low-power devices and cloud servers, have difficult networking, and collect sensitive data that deserves strong cryptography, but usually written by developers who have expertise in none of these areas. The goal of the research is to make it possible for two developers to build a complete, secure, Internet of Things applications in three months.The research focuses on four important principles. The first is "distributed model view controller." A developer writes an application as a distributed pipeline of model-view-controller systems. A model specifies what data the application generates and stores, while a new abstraction called a transform specifies how data moves from one model to another. The second is "embedded-gateway-cloud." A common architecture dominates Internet of Things applications. Embedded devices communicate with a gateway over low-power wireless. The gateway processes data and communicates with cloud systems in the broader Internet. Focusing distributed model view controller on this dominant architecture constrains the problem sufficiently to make problems, such as system security, tractable. The third is "end-to-end security." Data emerges encrypted from embedded devices and can only be decrypted by end user applications. Servers can compute on encrypted data, and many parties can collaboratively compute results without learning the input. Analysis of the data processing pipeline allows the system and runtime to assert and verify security properties of the whole application. The final principle is "software-defined hardware." Because designing new embedded device hardware is time consuming, developers rely on general, overkill solutions and ignore the resulting security implications. The data processing pipeline can be compiled into a prototype hardware design and supporting software as well as test cases, diagnostics, and a debugging methodology for a developer to bring up the new device. These principles are grounded in Ravel, a software framework that the team collaborates on, jointly contributes to, and integrates into their courses and curricula on cyberphysical systems.