CyberCorps Scholarship for Service: Empowering the Cybersecurity Workforce with a Focus on Artificial Intelligence

当前的网络安全格局突出了人工智能（AI）和机器学习（ML）的重要性，它们是传统安全措施在有效保护国家网络空间方面的关键增强。该项目旨在在拉斯维加斯的内华达州大学（UNLV）建立一个新的CyberCorps®服务奖学金（SFS）计划，以培养一批精通AI/ML的网络安全专家，为政府服务。UNLV课程整合了计算机科学和网络安全，并得到了专注于国家基础设施保护的AI/ML研究的支持。此外，该SFS计划旨在吸引和指导高素质的本科生和研究生，并积极与当地高中和社区学院合作，以加强人才管道。根据UNLV被公认为全国第四大多元化机构，并被指定为少数民族服务和西班牙裔服务机构，该计划将强调增加代表性不足和女学生在网络安全中的参与。该项目利用UNLV的现有资源和专业知识，使毕业生能够立即对政府网络安全角色产生影响。它体现了一种综合的教育方法，将理论知识与实践经验相结合，并发展软技能。学生通过学术课程，在线模块和行业认可的认证进行广泛的网络安全和AI/ML培训，所有这些都旨在使他们能够使用AI/ML技术检测，挫败和防止网络攻击。直接指导与专门的研究监督促进独立研究紧迫的网络安全挑战。此外，学生通过参加网络竞赛，参加会议，完成暑期实习，并通过独特的网络安全诊所计划获得真实世界的经验，在那里他们与实际客户合作，从而提高他们的实践能力。网络安全诊所还帮助学生提高他们的软技能，包括报告写作，公开演讲，项目管理和领导力。UNLV的学生还为针对高中生的网络安全教育计划做出贡献，并始终如一地参加联邦和工业网络安全活动。UNLV的多方面教育方法旨在培养全面的网络安全专业人员，准备立即为劳动力做出贡献。该项目由CyberCorps®服务奖学金（SFS）计划提供支持，该计划为建立或继续网络安全奖学金计划的提案提供资金，并与美国国家网络战略保持一致，以培养一支上级网络安全劳动力。毕业后，奖学金获得者需要在联邦，州，地方或部落政府组织的网络安全工作与他们的奖学金支持相同的时间。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

The current cybersecurity landscape highlights the importance of artificial intelligence (AI) and machine learning (ML) as critical enhancements to traditional security measures in effectively safeguarding the national cyberspace. This project aims to establish a new CyberCorps® Scholarship for Service (SFS) program at the University of Nevada, Las Vegas (UNLV) to cultivate a group of cybersecurity experts skilled in AI/ML for government service. The UNLV curriculum integrates computer science and cybersecurity and is bolstered by AI/ML research focused on national infrastructure protection. In addition, this SFS program is designed to attract and mentor high-caliber undergraduate and graduate students and proactively engage with local high schools and community colleges to fortify the talent pipeline. In line with UNLV's recognition as the nation's fourth most diverse institution and its designation as a Minority-serving and Hispanic-serving Institution, the program will emphasize increasing the participation of underrepresented and female students in cybersecurity. This project leverages UNLV's existing resources and expertise to equip graduates for an immediate impact in government cybersecurity roles. It embodies a comprehensive educational approach that merges theoretical knowledge with practical experiences and develops soft skills. Students engage in extensive cybersecurity and AI/ML training through academic coursework, online modules, and industry-recognized certifications, all designed to enable them to detect, thwart, and prevent cyber-attacks using AI/ML techniques. Direct mentorship with dedicated research supervision facilitate independent research into pressing cybersecurity challenges. Moreover, students refine their practical abilities by participating in cyber competitions, attending conferences, completing summer internships, and obtaining real-world experience through the unique cybersecurity clinic program, where they work with actual clients. The cybersecurity clinic also helps students improve their soft skills, including report writing, public speaking, project management, and leadership. UNLV students also contribute to cybersecurity educational initiatives aimed at high school students and consistently participate in federal and industrial cybersecurity events. UNLV’s multifaceted educational approach is designed to nurture well-rounded cybersecurity professionals prepared to contribute to the workforce immediately.This project is supported by the CyberCorps® Scholarship for Service (SFS) program, which funds proposals establishing or continuing scholarship programs in cybersecurity and aligns with the U.S. National Cyber Strategy to develop a superior cybersecurity workforce. Following graduation, scholarship recipients are required to work in cybersecurity for a federal, state, local, or tribal Government organization for the same duration as their scholarship support.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.