REU Site: CyberAI: Cybersecurity Solutions Leveraging Artificial Intelligence for Smart Systems

田纳西理工大学将为本科生提供一个新的研究体验（REU）网站，这将有助于各种智能系统的安全和隐私。拟议中的REU网站有一个为期三年的计划，为30名本科生提供研发（R&amp；D）活动的培训，重点是利用人工智能（AI）为智能系统提供网络安全解决方案。参与者将获得各个领域的知识，包括密码学，深度学习，联合和强化学习，基于图的异常检测和硬件攻击对策。在专家教师导师的指导下，学生将学习如何定义研究问题，开发，实施和评估解决方案。除了提高本科生的研究经验外，该网站旨在(1)促进网络安全劳动力的发展，(2)增加女性和少数民族学生在网络安全领域的代表性，(3)鼓励本科生攻读研究生，(4)支持TTU对网络安全研究的关注，以及(5)促进STEM招生。受人工智能、电信（如5G蜂窝网络）、传感技术和计算等领域最新进展的启发，智能电网和智能医疗等智能系统的概念应运而生，其目标是改善我们的日常生活。这些系统旨在革新所提供的服务，但它们也带来了安全和隐私方面的挑战。拟议中的REU站点将开展广泛的攻击研究，包括针对网络/硬件漏洞和安全/隐私保护的攻击。该网站将采用一系列工具，如深度学习、联邦学习、强化学习、密码学和基于图形的异常检测。本网站的主要研究成果将包括学术出版物、机器学习模型、模拟、教学手册等。在课程结束时，这些学生将拥有宝贵的知识和技能，有可能激发他们在网络安全领域从事专业职业的兴趣。鉴于目前网络安全专业人员的短缺，这是至关重要的，这与维护我们国家安全的必要性是一致的。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。

Tennessee Technological University will offer a renewed Research Experience for Undergraduates (REU) Site that will contribute to the security and privacy of various smart systems. The proposed REU site has a three-year plan to provide training to 30 undergraduate students in Research and Development (R&D) activities focused on cybersecurity solutions that leverage artificial intelligence (AI) for smart systems. Participants will gain knowledge in various areas, including cryptography, deep learning, federated and reinforcement learning, graph-based anomaly detection, and hardware attack countermeasures. Under the guidance of expert faculty mentors, students will learn how to define research problems, develop, implement, and evaluate solutions. In addition to enhancing the research experience for undergraduates, the site aims to (1) contribute to the cybersecurity workforce development, (2) increase the representation of female and minority students in cybersecurity, (3) encourage undergraduates to pursue graduate studies, (4) support TTU's focus on cybersecurity research, and (5) promote STEM enrollment.Inspired by recent advancements in AI, telecommunications (e.g., 5G cellular networks), sensing technologies, and computing, the concept of smart systems, such as smart power grids and smart healthcare, has emerged with the goal of enhancing our daily lives. These systems aim to revolutionize the services offered, but they also introduce security and privacy challenges. The proposed REU site will conduct research encompassing a wide range of attacks, including those targeting cyber/hardware vulnerabilities and security/privacy preservation. The site will employ an array of tools such as deep learning, federated learning, reinforcement learning, cryptography, and graph-based anomaly detection. The primary outcomes expected from this site's research efforts will include scholarly publications, machine learning models, simulations, instructional manuals, and more. By the end of the program, these students will possess valuable knowledge and skills, potentially igniting their interest in pursuing professional careers in the cybersecurity field. This is of paramount importance, given the existing shortage of cybersecurity professionals, and it aligns with the imperative of safeguarding our nation's security.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.