Collaborative Research: CyberTraining: Pilot: Interdisciplinary Training of Data-Centric Security and Resilience of Cyber-Physical Energy Infrastructures

在这个项目中，为学生和研究人员提供有指导的实践培训，结合电气工程、通信、科学和技术研究以及数据科学的专业知识。这为能源网络基础设施韧性教育建立了一种新的模式。开发的课程和教学材料将来自多个领域的高级技能整合到网络物理能源系统的保护伞下。学员使用独特的远程连接智能电网网络基础设施，开发和完善以数据为中心的能源行业所需的多学科技能。参与者扩展了他们的学术研究组合，增强了他们作为未来网络基础设施专业人员和用户的职业竞争力。为期两周的工作坊通过实验室演示和小型项目，让本科生/研究生和研究科学家沉浸在一个独特的培训机会中。该项目解决了三个主要的技术挑战：(I)在合作的大学之间建立一个新的远程连接的网络基础设施平台。现有的使用实时数字仿真器的半实物电力试验台与虚拟网络实验室相连，以表征网络-物理能源系统。组合的基础设施配备了最先进的硬件和软件模块，其中人、机器和电网可以在接近真实的学习环境中交互和协作。(2)在虚拟实验室中安装一个网络安全模块，以模拟网络威胁，如拒绝服务攻击和中间人攻击。参与者创建攻击场景，在这些场景中，攻击过程和结果可以在物理系统上可视化。(3)开发以机器学习为基础的数据分析技术，作为一套网络防御机制，例如数据驱动的敌对事件检测。参与者在攻击过程中执行他们的网络防御算法，这些防御的有效性使用测试台进行验证和可视化。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

In this project, students and researchers are provided with mentored, hands-on training combining expertise across electrical engineering, communication, science and technology studies, and data science. This establishes a novel model for energy cyberinfrastructure resilience education. The curriculum and instructional materials that are developed integrate advanced skills from multiple areas under the umbrella of cyber-physical energy systems. Participants develop and refine the multi-disciplinary skillsets needed for the data-centric energy industry using unique, remotely connected smart grid cyberinfrastructure. Participants extend their academic research portfolios, strengthening their career competitiveness as future cyberinfrastructure professionals and users. The two-week workshop immerses undergraduate/graduate students and research scientists in a unique training opportunity through laboratory demonstrations and mini projects. Three main technical challenges are tackled in the project: (i) Establishment of a new remotely connected cyberinfrastructure platform among the collaborating universities. An existing hardware-in-the-loop power testbed using a real-time digital simulator is connected with a virtual network laboratory to characterize cyber-physical energy systems. The combined infrastructure is equipped with state-of-the-art hardware and software modules, where humans, machines, and power girds can interact and cooperate in a near-to-real learning environment. (ii) Implementation of a cybersecurity module in the virtual lab to simulate cyber threats, such as denial-of-service attacks and man-in-the-middle attacks. Participants create attack scenarios that are played out, where the attacking process and consequence can be visualized on the physical system. (iii) Development of data analytics techniques based on machine learning as a set of cyber defense mechanisms, such as data-driven adversarial event detection. Participants execute their cyber defense algorithms alongside the attack, and the effectiveness of these defenses is validated and visualized using the testbed.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.