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

当前的网络安全格局突显了人工智能(AI)和机器学习(ML)作为对有效保护国家网络空间的传统安全措施的关键增强的重要性。该项目旨在内华达大学拉斯维加斯分校(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。联合国志愿人员的课程整合了计算机科学和网络安全，并得到了侧重于国家基础设施保护的人工智能/最大限度地研究的支持。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大学接触，以加强人才渠道。根据UNLV被公认为美国第四大最多元化的机构，并被指定为少数族裔服务机构和拉美裔服务机构，该计划将强调增加代表不足的女学生对网络安全的参与。该项目利用联合国志愿人员组织的现有资源和专门知识，使毕业生具备在政府网络安全方面立即发挥作用的能力。它体现了一种理论知识与实践经验相结合、培养软技能的综合教育方法。学生通过学术课程、在线模块和行业认可的认证参与广泛的网络安全和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。具有专门研究监督的直接指导有助于对紧迫的网络安全挑战进行独立研究。此外，学生还通过参加网络竞赛、参加会议、完成暑期实习以及通过与实际客户合作的独特网络安全诊所计划获得现实世界经验来提炼自己的实践能力。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。联合国志愿人员组织的学生还为针对高中生的网络安全教育倡议作出贡献，并持续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准备立即为劳动力做出贡献的全面发展的网络安全专业人员。该项目得到CyberCorps®服务奖学金(SFS)计划的支持，该计划为建立或继续开展网络安全奖学金计划提供资金，并与美国国家网络战略保持一致，以培养一支优秀的网络安全劳动力队伍。毕业后，奖学金获得者被要求在联邦、州、地方或部落政府组织的网络安全工作中工作，时间与他们的奖学金支持相同。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。

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.