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

在这个项目中，学生和研究人员提供了指导，实践培训结合专业知识跨越电气工程，通信，科学和技术研究，以及数据科学。 这为能源网络基础设施弹性教育建立了一个新的模式。开发的课程和教学材料整合了网络物理能源系统下多个领域的先进技能。参与者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，加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。为期两周的研讨会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独特的培训机会中。该项目应对三个主要技术挑战：㈠在合作大学之间建立一个新的远程连接网络基础设施平台。使用实时数字仿真器的现有硬件在环功率测试平台与虚拟网络实验室连接，以表征网络物理能量系统。组合的基础设施配备了最先进的硬件和软件模块，人类，机器和电网可以在接近真实的学习环境中进行交互和合作。(ii)在虚拟实验室中实施网络安全模块，以模拟网络威胁，例如拒绝服务攻击和中间人攻击。参与者创建攻击场景，在其中攻击过程和后果可以在物理系统上可视化。(iii)开发基于机器学习的数据分析技术，作为一套网络防御机制，例如数据驱动的对抗性事件检测。该奖项反映了NSF的法定使命，通过使用基金会的知识价值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.