REU Site: Machine Learning in Cybersecurity

这笔资金在宾夕法尼亚州立大学建立了一个新的本科生研究体验(REU)网站。一个由经验丰富的教师导师组成的跨学科团队将指导本科生完成夏季研究项目，重点是应用机器学习方法来解决网络安全问题，特别是网络攻击。科学、政府和商业领域产生的数据量和复杂性急剧增加，利用数据漏洞的网络相关攻击日益频繁，这使得网络安全成为国家的关键优先事项。该网站每年夏天将招募9名学生，他们将从事具有挑战性和重要性的研究项目。该项目团队将利用历史上黑人学院和大学以及西班牙裔服务机构的合作者网络，招募代表人数不足的少数族裔的学生参加REU网站。这些学生还将参与其他专业发展，这将有助于他们为研究生学习和计算机职业生涯做好准备。这个项目的智力价值在于专注于机器学习和网络安全，强大的教师团队指导研究，以及学生将使用的最先进的实验室设施。随着网络对手和攻击者留下的数字足迹的数量和复杂性迅速增加，防御机制需要能够最大限度地处理和利用大量数据。该网站将致力于这一领域的重要问题，并可能对网络安全研究的知识体系做出贡献。该奖项反映了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。

This funding establishes a new Research Experiences for Undergraduates (REU) Site at Pennsylvania State University. An interdisciplinary team of experienced faculty mentors will guide undergraduate students in summer research projects focused on applying machine learning methods to solve cybersecurity problems, particularly cyber attacks. The dramatic increase in the amount of data and complexity of data generated in sciences, government, and the business world and the increasing frequency of cyber-related attacks exploiting the vulnerabilities of the data, have made cybersecurity a critical national priority. The site will recruit a cohort of 9 students each summer who will work on research projects that are challenging and important. The project team will use a network of collaborators at Historically Black Colleges and Universities and at Hispanic-Serving Institutions to recruit students from under-represented minorities to participate in the REU Site. The students will also participate in other professional development that will help prepare them for graduate studies and careers in computing. The intellectual merit of this project lies in the focus on machine learning and cybersecurity and the strong faculty group guiding the research as well as the state-of-the art laboratory facilities the students will use. As the amount and complexity of the digital footprints that cyber adversaries and attackers leave behind rapidly increase, defense mechanisms need to be able to handle and exploit the large amount of data to the fullest. This site will work on important problems in this area and can potentially contribute to the body of knowledge of cybersecurity research.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.