REU Site: Undergraduate Research Experience for Women in Machine Learning-based Cybersecurity

REU 网站：基于机器学习的网络安全领域女性本科生研究经验

• 批准号: 2244597
• 负责人: Younghee Park
• 金额: $ 37.4万
• 依托单位: San Jose State University Foundation
• 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
• 起止时间: 2023-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2244597&HistoricalAwards=false
• 关键词: REU; Site; Undergraduate; Research; Experience

This project will establish a Research Experiences for Undergraduates (REU) Site at San Jose State University, a Hispanic-serving institute that provides machine learning-based cybersecurity research experience for women. Cybersecurity is of fundamental importance to the economic strength and national security of the United States in order to form a safe and innovative foundation in cyberspace. This project contributes to the future cybersecurity workforce development while the REU site focuses on diversity and quality of cybersecurity workforce education through training female students in newly emerging cybersecurity topics under close mentorships. This REU program will improve their cybersecurity research skills through well-defined project problem sets based on machine learning (ML) and deep learning (DL)-based cybersecurity techniques. This program will have the following societal impacts. (1) The research in the REU site will train minority students to improve their cybersecurity skills through intensive research training in ML/DL-based cybersecurity techniques. (2) The hands-on lab exercises to understand each research topic will help forge the path for students to pursue careers in cybersecurity. (3) This program can drive the broad participation of women in cybersecurity and reduce the gender gap in cybersecurity fields.The REU research projects include various important research topics in ML/DL-based cybersecurity techniques in the different research areas. In particular, the REU site focuses on training women in ML/DL-based cybersecurity research areas according to the following ultimate goals: (1) engaging female students with the real-world security challenges in emerging cybersecurity topics in malware analysis, network data analysis, and social engineering data analysis, (2) initiating and supporting discussions and collaborations with academic mentors to improve awareness, education, and research in the ML/DL-based cybersecurity problems, (3) enhancing cybersecurity skillsets through well-defined cybersecurity research projects in important topics, and (4) developing their professional career with experts from academia and industry that can cover data science techniques and cybersecurity areas. The research projects aim (1) to train students in new important cybersecurity problems in the new areas through our faculty research outcomes for their skill improvements and (2) to build up research capabilities in cybersecurity fields through hands-on exercises with our existing labs that each faculty mentor has. Related software and research materials will be made available on the project website.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.

该项目将在圣何塞州立大学建立一个本科生研究经验（REU）站点，这是一个为西班牙裔服务的研究所，为女性提供基于机器学习的网络安全研究经验。网络安全对美国的经济实力和国家安全至关重要，以形成安全创新的网络空间基础。该项目有助于未来网络安全劳动力的发展，而REU网站通过在密切指导下培训女学生新兴网络安全主题，专注于网络安全劳动力教育的多样性和质量。该REU计划将通过基于机器学习（ML）和深度学习（DL）的网络安全技术的定义良好的项目问题集来提高他们的网络安全研究技能。这个项目将产生以下社会影响。(1) REU网站的研究将通过基于ML/ dl的网络安全技术的强化研究培训，培养少数民族学生提高网络安全技能。(2)理解每个研究课题的动手实验练习将有助于为学生在网络安全领域的职业生涯铺平道路。(3)推动女性广泛参与网络安全领域，缩小网络安全领域的性别差距。REU的研究项目包括不同研究领域中基于ML/ dl的网络安全技术的各种重要研究课题。特别是，REU网站专注于根据以下最终目标在基于ML/ dl的网络安全研究领域培训女性：(1)让女学生参与恶意软件分析、网络数据分析和社会工程数据分析等新兴网络安全主题的现实安全挑战；(2)发起并支持与学术导师的讨论和合作，以提高对基于ML/ dl的网络安全问题的认识、教育和研究；(3)通过明确定义的重要主题的网络安全研究项目提高网络安全技能。(4)与涵盖数据科学技术和网络安全领域的学术界和产业界专家一起发展自己的职业生涯。这些研究项目旨在(1)通过我们教师的研究成果，培养学生在新领域的新的重要网络安全问题，以提高他们的技能；(2)通过每位教师导师在我们现有实验室的实践练习，建立网络安全领域的研究能力。相关软件和研究资料将在项目网站上提供。该奖项反映了美国国家科学基金会的法定使命，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。