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REU Site: Research Experience in Cyber-Security for Cyber-Physical Systems

REU Site: Research Experience in Cyber-Security for Cyber-Physical Systems
REU 网站:网络物理系统网络安全研究经验
批准号:
1757659
负责人:
Jeremy Straub
金额:
$36.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-03-01 至 2022-02-28

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中文摘要
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英文摘要
This research experience for undergraduates (REU) site has a focus on security of cyber-physical systems such as self-driving cars, unmanned aerial vehicle systems, robots, smart electrical grid systems and internet of things devices that are among the most important devices to secure due to their real-world interaction with humans, other equipment and the environment. These devices are also critical to manufacturing efficiency and national competitiveness. This program provides student participants an opportunity to gain experience in developing and analyzing cyber-security-related software for such cyber-physical systems. Through this experience, students learn about the process of and techniques for conducting research in cybersecurity, cyber-physical systems and the computing disciplines in general. They also come to better understand their own capabilities and interest in pursuing research careers, refining and potentially changing their career and educational goals.  The project, thus, promotes the progress of science by allowing students to evaluate the pursuit of careers in research through immersive participation in a real-world research environment, and it advances national security and welfare through its focus on the area of cybersecurity.  The projects focusing on topics such as self-driving cars and robots excite student participants and provide the opportunity for hands on work with hardware, allowing students to see the effect of decisions they have made regarding software design and security. Sample projects involve 1) the design of secure coordination systems, intrusion, and malicious data detection, 2) issue prevention and detection, 3) data trustworthiness, 4) sensor data trust assessment, and 5) supervisory control and data acquisition system security, and reliability analytics. Through these, students gain exposure to multiple sub-disciplines related to these projects, allowing them to experience in multiple related areas. They also gain an appreciation for the importance of each sub-discipline as well as the opportunity to work on a large project from start to finish in conjunction with their cadre-mates. Participating students complete research projects, including software development, results analysis and technical write-ups.  They are mentored by North Dakota State University faculty through cadre-group, scheduled one-on-one and ad-hoc meetings.  They gain appreciation of the importance of quality assurance processes, particularly for ensuring software security and the safety of cyber-physical systems, and they learn about the software lifecycle and proper software development practices.  The projects are designed so that students, despite working on their own research goal and serving as the "lead scientist" on this goal, rely on other students for their success.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.
期刊论文(31)
专著(0)
科研奖励(0)
会议论文
Development of a 'fake news' machine learning classifier and a dataset for its testing
开发“假新闻”机器学习分类器及其测试数据集
DOI: 10.1117/12.2520131
发表时间: 2019
期刊: Proceedings of SPIE
影响因子: --
作者: [Fleck, William, Snell, Nicholas, Traylor, Terry, Straub, Jeremy]
通讯作者: Straub, Jeremy
Assessment of a Hybrid Research Experience for Undergraduates Program During the COVID-19 Pandemic
COVID-19 大流行期间本科生混合研究体验项目评估
DOI: --
发表时间: 2022
期刊: Proceedings of the 2022 ASEE Annual Conference
影响因子: --
作者: [Straub, Jeremy]
通讯作者: Straub, Jeremy
Human Male Body Images from Multiple Perspectives with Multiple Lighting Settings
多种照明设置下多视角的男性身体图像
DOI: 10.3390/data4010003
发表时间: 2019
期刊: Data
影响因子: 2.6
作者: [Clemons, William, Straub, Jeremy]
通讯作者: Straub, Jeremy
Gradient descent training expert system
梯度下降训练专家系统
DOI: 10.1016/j.simpa.2021.100121
发表时间: 2021
期刊: Software Impacts
影响因子: --
作者: [Straub, Jeremy]
通讯作者: Straub, Jeremy
27
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