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

这一奖项更新了老道明大学本科生研究经验(REU)网站。REU网站由该大学网络安全教育和研究中心(CCSER)的教职员工领导。CCSER包括来自全校大量系和学院的教职员工，这些教职员工可以提供多学科研究项目，专注于应用深度学习技术来解决广泛的网络安全问题。网络安全已经成为我们社会普遍存在的一个重要问题。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网站将在夏季接待来自全国各地的本科生进行研究。该网站计划每年招收不同类型的本科生，特别是面向传统上在计算机领域代表性不足的群体，以及来自本科研究机会有限的机构的学生。这些学生还将参加其他职业发展活动，为他们进入计算机劳动力市场和可能成为研究人员做好准备。REU网站由网络安全教育和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，应该能为本科生提供引人注目的研究体验。这个REU网站为本科生在固有的多学科网络安全学科中提供了独特的学习和研究机会。学生将使用深度学习技术来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。与网络安全相关的数据和信息的海量和复杂性质往往需要现代人工智能技术，如用于处理、检测、分析和识别的深度学习，作为网络安全研究的一部分。因此，这个网站有潜力解决对为我们国家提供网络安全来说及时和关键的问题。这个奖项反映了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 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.