REU Site: Deep Learning Driven Cybersecurity Research in a Multidisciplinary Environment

该奖项更新了老道明大学的本科生研究经历（REU）网站。REU网站由该大学网络安全教育与研究中心（CCSER）的教师领导。CCSER包括来自大学众多院系和学院的教师，他们可以提供多学科研究项目，重点是应用深度学习技术解决广泛的网络安全问题。网络安全已成为当今社会普遍存在的重要问题。机器学习为解决网络安全问题和开发更强大、更安全的系统和网络基础设施提供了独特的新方法。REU网站将接待来自全国各地的本科生在夏季进行研究。该网站计划每年招收一批不同的本科生，特别是针对那些传统上在计算机领域代表性不足的群体和本科生研究机会有限的机构的学生。学生们还将参加其他专业发展活动，为进入计算机行业和未来可能成为研究人员做准备。REU网站由网络安全教育与研究中心的教师导师领导。该中心的教师拥有重要的研究专业知识，并提供最先进的设施，应该为本科生提供引人注目的研究经验。这个REU网站提供了独特的学习和研究机会，本科生在本质上多学科的网络安全学科。学生将使用深度学习技术解决移动和网络安全、恶意软件、物联网安全、风险管理和人为因素等领域的问题。网络安全相关数据和信息的巨大和复杂性往往需要现代人工智能技术，如深度学习来处理、检测、分析和识别，作为网络安全研究的一部分。因此，这个网站有潜力及时解决为我们国家提供网络安全的关键问题。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。

This award renews a Research Experiences for Undergraduates (REU) Site at Old Dominion University. The REU Site is led by faculty from the Center for Cybersecurity Education and Research (CCSER) at the university. CCSER includes faculty from a large number of departments and colleges across the university that can provide multidisciplinary research projects that focus on applying deep learning techniques to solve a broad range of cybersecurity problems. Cybersecurity has become an important pervasive issue to our society. Machine learning offers unique new ways to approach cybersecurity problems and develop more robust and secure systems and cyberinfrastructure. The REU Site will host undergraduate students from across the nation to conduct research during the summer. The site plans to recruit a diverse cohort of undergraduate students each year, particularly targeting students from groups traditionally under-represented in computing and from institutions where undergraduate research opportunities are limited. The students will also participate in other professional development activities that will prepare them for entering the computing workforce and for possible futures as researchers.The REU site is led by faculty mentors from the Center for Cybersecurity Education and Research. The faculty of the Center have significant research expertise and offer state-of-the-art facilities that should provide compelling research experiences to undergraduates. This REU Site offers unique learning and research opportunities for undergraduate students in the inherently multidisciplinary cybersecurity discipline. Students will use deep learning technologies to solve problems in areas such as mobile and network security, malware, Internet of Things security, risk management, and human factors. The huge and complex nature of cyber-security-related data and information often requires modern artificial intelligence techniques such as deep learning for processing, detection, analysis, and recognition as part of cybersecurity research. Thus, this site has the potential to address problems that are timely and critical to providing cybersecurity for our nation.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.