cpss marvell_用于网络物理系统安全（CPSS）的数字孪生_网络_weixin

cpss marvell

While the term “digital twin” typically refers to a data-driven physical model of a system, it can also be used to describe an emulated or simulated device that may be connected to an emulated network.

尽管术语“数字孪生”通常是指系统的数据驱动物理模型，但它也可以用于描述可以连接到仿真网络的仿真或仿真设备。

The Digital Twin is a computer model that reflects and simulates the real object and its interactions with its surroundings, providing a more accurate representation of the shape and shape of the object than a physical replica. The method of replicating physical objects is still in its infancy, and it requires specific technology and equipment to succeed.

Digital Twin是一种计算机模型，可以反射和模拟真实对象及其与周围环境的相互作用，比物理副本提供更精确的对象形状和形状表示。复制物理对象的方法仍处于起步阶段，它需要特定的技术和设备才能成功。

Digital twins are simple; they act as a bridge between the physical and digital worlds by using sensors to collect real-time data on physical objects. This data is used to create digital duplicates of these objects, which make it possible to understand, analyze, manipulate, and optimize them.

数字双胞胎很简单；通过使用传感器收集有关物理对象的实时数据，它们充当了物理世界和数字世界之间的桥梁。此数据用于创建这些对象的数字副本，从而可以理解，分析，操纵和优化它们。

The digital twins, combined with other technologies such as cloud computing, artificial intelligence, and machine learning, will track, monitor, and optimize the flow of goods from factories around the world. Increased availability of cloud computing, analytics, and data analytics services is a key factor for the digital twins. With cloud-based platforms for IoT and analytics software, companies are investing in cloud-based analytics platforms that enable them to capitalize on the “digital twin” trend. These investments are designed to optimize the integration of data from various sources such as the cloud, mobile devices, cloud services, data centers, or even physical systems.

数字双胞胎与云计算，人工智能和机器学习等其他技术相结合，将跟踪，监控和优化全球工厂的货物流向。云计算，分析和数据分析服务的可用性提高是数字双胞胎的关键因素。借助用于物联网和分析软件的基于云的平台，公司正在投资基于云的分析平台，以使其能够利用“数字孪生”趋势。这些投资旨在优化来自各种来源(例如云，移动设备，云服务，数据中心甚至物理系统)的数据集成。

To create a digital twin of a physical asset, engineers collect and synthesize data from a variety of sources, including sensors and physical components of physical assets such as buildings, cars, vehicles, and other physical objects. This information and AI algorithms are integrated into a virtual model based on physics. By applying analytics to this model, we obtain the best possible analysis and insights about the asset. The consistent flow of data helps us to gain relevant insights about the assets and use them correctly, which contributes to optimizing business results.

为了创建实物资产的数字孪生，工程师从各种来源收集和综合数据，包括传感器和实物资产的物理组件，例如建筑物，汽车，车辆和其他实物。该信息和AI算法被集成到基于物理的虚拟模型中。通过将分析应用于该模型，我们可以获得有关资产的最佳分析和见解。一致的数据流有助于我们获得有关资产的相关见解并正确使用它们，从而有助于优化业务成果。

The concept of creating twins as tools to improve decision-making has long been used in engineering. Multiple technologies, including computer vision, artificial intelligence, machine learning, and advanced simulation, make it possible to create a virtual version of a physical asset using the same physical components, sensors, and components. Advanced simulations can use the largest and most complex scales and work in real-time to solve the most important problems in the design, construction, operation, and maintenance of complex systems.

长期以来，将双胞胎作为改善决策的工具的概念已在工程学中使用。包括计算机视觉，人工智能，机器学习和高级仿真在内的多种技术使使用相同的物理组件，传感器和组件创建物理资产的虚拟版本成为可能。先进的仿真可以使用最大和最复杂的比例并实时工作，以解决复杂系统的设计，构造，操作和维护中最重要的问题。

A fully developed digital replica can be built in real-time, as used for future testing, development, and experimentation. Simply put, this is a digital replica clone that allows manufacturers to interact with digital platforms and perform tests on real physical twins in reality.

可以实时构建完整开发的数字副本，以用于将来的测试，开发和实验。简而言之，这是一个数字副本克隆，允许制造商与数字平台进行交互，并在实际的实际双胞胎上进行测试。

Currently, the most efficient way to do this is to attach structural sensors that act as boundaries to help the digital platform accurately replicate shape, and object.

当前，最有效的方法是连接充当边界的结构传感器，以帮助数字平台准确复制形状和对象。

By iteratively modeling changes and testing the functioning of components and systems, digital twins can save time and money by cost-effective troubleshooting and correcting disruptions in the virtual world in real-time. More than just visualization, the digital twin can build consensus and accelerate innovation. Connected digital things generate real-time data, and this helps companies predict problems early, warn early, prevent downtime, develop new opportunities, and plan better products for the future, even at a lower cost than simulation.

通过对变更进行建模并测试组件和系统的功能，数字孪生可以通过经济高效的故障排除和实时纠正虚拟世界中的中断来节省时间和金钱。数字孪生不只是可视化，还可以建立共识并加速创新。互联的数字事物可以生成实时数据，这可以帮助公司及早预测问题，及早发出警告，防止停机，开发新机会并为未来计划更好的产品，即使其成本低于仿真。

Similar to the advantages of manufacturing, digital twins can revolutionize the design and production of powerful, high-performance components for industrial applications.

与制造的优势相似，数字孪生可以彻底改变工业应用中功能强大的高性能组件的设计和生产。

For its Apollo program (around 60s and 70s), NASA has developed two identical spacecraft that reflect conditions in space and on Earth for training and flight preparation.

对于其阿波罗计划(大约60年代和70年代)，美国宇航局开发了两种相同的航天器，它们可以反映太空和地球上的状况，以进行训练和飞行准备。

The digital twin is also a component of cyber-physical systems. The digital twin model enables the integration of physical and virtual physical systems into the cyber-physical security model of a cyber-system.

数字孪生也是网络物理系统的组成部分。数字孪生模型可以将物理和虚拟物理系统集成到网络系统的网络物理安全模型中。

The introduction of CPPS (Cyber-Physical Production Systems) enables smart factories to assist in various decision-making processes by predicting the future based on past and present situations. CPPS consist of independent and cooperative elements integrated to the Industrial Internet of Things to create Smart Factories, which face efficiently to demands of the multifaceted MS (Manufacturing Systems) control. IoT refers to wireless communication capabilities integrated with sensors and computers that allow data to be collected on uniquely identifiable objects over the Internet. CPPS, one of the few core technologies needed to build a smart factory.

CPPS(网络物理生产系统)的引入使智能工厂可以根据过去和现在的情况预测未来，从而协助各种决策过程。 CPPS由集成到工业物联网中以创建智能工厂的独立和协作元素组成，这些工厂可以有效应对多方面MS(制造系统)控制的需求。物联网是指与传感器和计算机集成的无线通信功能，该功能允许通过Internet在唯一可识别的对象上收集数据。 CPPS是构建智能工厂所需的少数核心技术之一。

In these futuristic factories, connected devices can sense their surroundings and interact with each other to make decentralized decisions. This is similar to the run-and-run simulation scenarios that are often seen in science fiction movies, where every possible scenario is proved.

在这些未来工厂中，连接的设备可以感知周围环境并相互交互以做出分散决策。这类似于科幻电影中经常出现的运行模拟场景，其中证明了每种可能的场景。

Previous studies suggest that the common components of CPSs (Cyber-physical systems) and CPPs (Cyber-physical Platform) include electronic hardware, software, and digital twins that are interconnected in the real and virtual worlds. The digital twin concept can be applied by organizations to cyber-systems and physical OT systems by linking probabilistic engineering models with test, operational, and maintenance data to evaluate the security of their physical and virtual physical systems. Digital system models offer OT and IT engineers, stakeholders the opportunity to examine the potential risks and benefits of cyber systems that should be considered throughout the life cycle.

先前的研究表明，CPS(网络物理系统)和CPP(网络物理平台)的常见组件包括在现实世界和虚拟世界中互连的电子硬件，软件和数字孪生。通过将概率工程模型与测试，运营和维护数据链接起来，以评估其物理和虚拟物理系统的安全性，组织可以将数字孪生概念应用于网络系统和物理OT系统。数字系统模型为OT和IT工程师，利益相关者提供了检查整个生命周期中应考虑的网络系统潜在风险和收益的机会。

It also helps to conduct predictive assessments of future capabilities to influence the design and implementation of cyber-physical and virtual physical security solutions for cyber systems.

它还有助于对未来能力进行预测性评估，以影响网络系统的网络物理和虚拟物理安全解决方案的设计和实施。

Designers need to figure out where things are going and how they should work before they are used physically. IoT deployment is digital twins optimized for both physical and digital security, as well as for the security of the devices themselves.

设计人员需要在实际使用之前弄清楚事情的发展方向和工作方式。物联网部署是针对物理和数字安全性以及设备本身安全性进行优化的数字孪生兄弟。

Essentially, the digital twin acts as a virtual version of the physical asset with the same physical components. Using data on how each part of a system reacts to the environment, supported by data provided by sensors in the physical world, its digital twins can simulate and analyze real-world conditions and respond to operational changes.

本质上，数字孪生是具有相同物理组件的物理资产的虚拟版本。利用由物理世界中的传感器提供的数据支持的有关系统各部分如何对环境做出React的数据，其数字双胞胎可以模拟和分析现实条件并响应操作变化。

Modern aircraft engines can have thousands or tens of thousands of sensors and generate terabytes of data per second. In the coming years, it is expected the widespread use of digital twins in industries with multiple use cases. They could be digitally designed and tested before being physically manufactured. Market research firm Gartner has dubbed IoT a “digital twin” and estimates that digital twins will represent a billion things in three to five years. Organizations planning to use IoT should consider the digital twin as essential technology, as it provides a bridge between the physical and digital worlds. By 2021, GE will have more than $1.8 billion in annual revenue from its digital twin businesses.

现代飞机发动机可以具有成千上万的传感器，每秒可生成TB级的数据。在未来的几年中，预计数字双胞胎将在具有多个用例的行业中得到广泛使用。它们可以在进行物理制造之前进行数字化设计和测试。市场研究公司Gartner将物联网称为“数字孪生”，并估计数字孪生将在三到五年内代表十亿个事物。计划使用物联网的组织应将数字孪生技术视为必不可少的技术，因为它提供了物理世界和数字世界之间的桥梁。到2021年，GE的数字孪生业务年收入将超过18亿美元。

In the context of our research, digital twins reflect the needs of experts in industrial automation who state the need for a high level of understanding of the physical and virtual components of a system. Since the digital twin runs in an isolated virtual environment, it can be analyzed without risking disturbances to living systems. Therefore, malicious behavior or errors may be indicated by the presence or absence of physical components within the virtual twin rather than by a physical component. An integrated virtual model means that conventional control systems can no longer be leveraged. We assume that the digital twins will not cause problems in the long term, but they will.

在我们的研究背景下，数字双胞胎反映了工业自动化专家的需求，他们表示需要对系统的物理和虚拟组件有较高的了解。由于数字双胞胎在隔离的虚拟环境中运行，因此可以对其进行分析，而不必担心会干扰生命系统。因此，恶意行为或错误可以通过虚拟双胞胎中是否存在物理组件而不是物理组件来指示。集成的虚拟模型意味着无法再利用传统的控制系统。我们假设数字双胞胎从长远来看不会造成问题，但是会造成问题。

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