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（San Jose State University）的本科生（REU）网站建立研究经验，这是一家西班牙裔服务学院，为妇女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，以便在网络空间构成安全，创新的基础。该项目为未来的网络安全劳动力发展做出了贡献，而REU网站通过培训在近距离指导下的新兴网络安全主题中培训女性学生的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）和基于深度学习（DL）基于基于的网络安全技术的项目问题集来提高其网络安全研究技能。该计划将产生以下社会影响。 （1）REU网站的研究将通过基于ML/DL的网络安全技术进行深入的研究培训来培训少数民族学生，以提高其网络安全技能。 （2）动手实验室练习以了解每个研究主题，将有助于为学生从事网络安全职业的道路。 （3）该计划可以推动妇女在网络安全方面的广泛参与，并减少网络安全领域的性别差距。REU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主题。 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网络安全问题，（3）通过重要主题中定义明确的网络安全研究项目来增强网络安全技能，（4）（4）通过学术界和行业的专家发展他们的职业生涯，这些专家可以涵盖数据科学技术和网络安全领域。研究项目的目的（1）旨在通过我们的教师研究成果来培训新领域中新的重要网络安全问题，以提高他们的技能，（2）通过与我们现有教师的现有实验室的动手练习来建立网络安全领域的研究能力。相关的软件和研究材料将在项目网站上提供。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来提供支持。