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

该奖项更新了旧自治领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）的教师领导。 CCSER包括来自大学众多院系的教师，他们可以提供多学科的研究项目，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的一个重要的普遍问题。 机器学习提供了独特的新方法来解决网络安全问题，并开发更强大、更安全的系统和网络基础设施。 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多样化的本科生，特别是针对传统上在计算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。 学生还将参加其他专业发展活动，为他们进入计算劳动力市场和未来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。该中心的教师有显著的研究专业知识，并提供国家的最先进的设施，应该提供引人注目的研究经验，本科生。这个REU网站提供了独特的学习和研究机会，本科生在固有的多学科网络安全学科。学生将使用深度学习技术解决移动的和网络安全、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庞大和复杂性通常需要现代人工智能技术，如深度学习，以处理，检测，分析和识别，作为网络安全研究的一部分。因此，这个网站有潜力解决问题，是及时和关键提供网络安全为我们的国家。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的知识价值和更广泛的影响审查标准的支持。

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.