Collaborative Research: CyberTraining: Implementation: Small: Train the Trainers as Next Generation Leaders in Data Science for Cybersecurity for Underrepresented Communities
Collaborative Research: CyberTraining: Implementation: Small: Train the Trainers as Next Generation Leaders in Data Science for Cybersecurity for Underrepresented Communities
批准号:
2321110
负责人:
Yunpeng Zhang
金额:
$32.52万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-15 至 2026-08-31
中文摘要
拥有数据科学和网络安全整合专业知识的劳动力对于保持美国在全球竞技场的竞争力和安全至关重要。培训师,包括教师和专业人士,谁是配备了数据科学和网络安全技能都在高需求,以发挥领导作用,在代表性不足的社区,并生成数据驱动的,强大的解决方案,以应对各种挑战。该项目旨在通过项目团队在三所少数民族服务大学的合作努力来满足这一迫切需求,这些大学具有强大的区域影响力:休斯顿大学(UH),草原景观大学(PVAMU)和亚拉巴马大学(AAMU)。该项目的总体目标是将培训师培养为代表性不足的社区的数据科学网络安全的下一代领导者,为他们提供知识和技能,将这些技术传授给他们的学生和同龄人。该项目探索了数据科学网络安全领域的教学,材料,工具和培训环境的创新方法。具体而言,该项目的贡献是:a)提高参与机构在数据科学和网络安全领域的研究能力,促进HBCU招聘和留住高素质的研究人员; B)更新本科生和研究生课程,采用新的数据科学促进网络安全教学模块,以反映最新进展和最佳实践; c)通过培训人员提高非裔美国人和其他少数民族学生对数据科学促进网络安全的挑战和机遇的认识; d)开发新的课程材料和源代码,并促进项目成果的广泛传播。该项目还通过其研讨会系列为来自广泛学科的学习者扩展了教育优势,从而在医疗保健,绿色能源,智能城市和制造业等各个行业中更大程度地采用数据科学。该项目致力于推进网络安全数据科学领域的学科教育研究领域。该奖项反映了NSF的法定使命,并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。
英文摘要
A workforce with expertise in the integration of Data Science and Cybersecurity is crucial to maintaining the United States' competitiveness and security in the global arena. Trainers, including faculty and professionals, who are well equipped with both Data Science and Cybersecurity skills are in high demand in order to play leadership roles in underrepresented communities and generate data-driven, robust solutions to various challenges. The project is designed to address this immediate need with the collaborative efforts from the project team across three minority-serving universities with a strong regional presence: University of Houston (UH), Prairie View A&M University (PVAMU), and Alabama A&M University (AAMU). The overarching goal of this project is to train the trainers as next generation leaders in Data Science for Cybersecurity for underrepresented communities, providing them with the knowledge and skills to impart these techniques to their students and peers. This project explores innovative approaches in teaching, materials, tools, and training environments in the Data Science for Cybersecurity field. Specifically, the contributions of this project are a) enhance the research capabilities of the participating institutions in the areas of Data Science and Cybersecurity, promoting recruitment and retention of highly qualified researchers at HBCUs; b) update undergraduate and graduate curricula with new Data Science for Cybersecurity teaching modules to reflect the latest advances and best practices; c) raise awareness among African American and other minoritizy students through trainers of the challenges and opportunities in Data Science for Cybersecurity; and d) develop new course materials and source code and facilitate the widespread dissemination of the project results. The project also expands the educational benefits through its workshop series to learners from a wide range of disciplines, leading to the potential greater adoption of Data Science in various industries such as healthcare, green energy, smart cities, and manufacturing. The project is dedicated to advancing the field of discipline-based education research in the areas of Data Science for Cybersecurity.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.
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