Collaborative Research: CISE-MSI: RPEP: SaTC: HBCU Artificial Intelligence and Cybersecurity (AI-CyS) Research Partnership

合作研究：CISE-MSI：RPEP：SaTC：HBCU 人工智能和网络安全 (AI-CyS) 研究合作伙伴

• 批准号: 2131256
• 负责人: Idongesit Mkpong-Ruffin
• 金额: $ 15.99万
• 依托单位: Florida Agricultural and Mechanical University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-11-01 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2131256&HistoricalAwards=false
• 关键词: Collaborative; Research; CISE; MSI; RPEP

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This project brings together researchers from seven Historically Black Colleges and Universities (HBCUs) and three National Research Laboratories (NRLs) to develop the AI-CyS research partnership at the intersection of artificial intelligence (AI) and cybersecurity. Cybersecurity vulnerabilities are growing at a scale and speed that strains human capacity to proactively address threats; developing AI and machine learning (ML) techniques to support prediction and detection capabilities is thus an important area of research. The HBCUs involved in AI-CyS either already have or are rapidly developing cybersecurity research capacity that would be further developed by increasing student and faculty involvement and training. To develop that potential, the project team will leverage its existing research activities and collaborations to deepen relationships with both other HBCUs and with the NRLs. The NRLs will provide additional research resources and mentoring through both regular remote meetings and on-site visits to the NRLs around projects of mutual interest, and opportunities for student internships and faculty visits at the NRLs. The team will also work to expand the impact of the partnership by (a) hosting an annual research conference to bring researchers together across the partners, (b) adding additional research projects, HBCUs and national lab partners with complementary research and educational interests to the existing partnership, and (c) developing cross-university curricula and mentoring programs to train HBCU students to be future research and workforce leaders in cybersecurity. Together, these efforts will advance research in cybersecurity, research capacity at the partner institutions, and research and educational opportunities for students at HBCUs, who are often members of underrepresented groups in computing. The partnership will be organized around five seed research projects chosen to maximize existing capacity and collaborations. The first will use reinforcement learning to improve target selection by current autonomous network mapping software agents. The second involves analyzing network traceroute data to better understand and work around limitations of its ability to map paths in order to better detect and classify network anomalies. The third focuses on developing, then defending against, adversarial attacks on computer vision algorithms in which attackers add visual patches to objects to fool object detection and classification tools. The fourth will analyze existing tools and algorithms for generating “deepfake” videos to develop methods to detect forged video in near real-time, with applications to surveillance and authentication tasks. The fifth will extend probabilistic sequential models to develop threat detectors at multiple levels of the network stack in the context of Internet of Things devices. Beyond these specific seed research projects, the project team will also analyze its activities to develop evidence-based best practices for research capacity-building efforts. These efforts will include developing mechanisms to expand current collaborations and foster resources, sharing expertise between HBCU members, and hosting an annual research conference that allows faculty and students from both current and potential partner HBCUs to showcase their cybersecurity research and create connections to other researchers and resources.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.

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This project brings together researchers from seven Historically Black Colleges and Universities (HBCUs) and three National Research Laboratories (NRLs) to develop the AI-CyS research partnership at the intersection of artificial intelligence (AI) and cybersecurity.网络安全脆弱性正在以规模和速度增长，使人类积极应对威胁的能力构成影响；因此，开发AI和机器学习（ML）技术来支持预测和检测功能是重要的研究领域。参与AI-CYS的HBCU已经具有或正在迅速发展的网络安全研究能力，这将通过增加学生和教职员工的参与和培训而进一步发展。为了发展潜力，项目团队将利用其现有的研究活动和合作来加深与其他HBCU和NRL的关系。 NRL将通过定期远程会议和对NRL的互惠互利项目以及NRLS的学生实习和教师访问的机会提供其他研究资源和心理。该团队还将通过（a）举办年度研究会议来扩大合作伙伴关系的影响，以使研究人员团结在一起，（b）增加其他研究项目，HBCUS和国家实验室合作伙伴，具有完整的研究和教育兴趣，并（c）（c）跨国公司课程和精神计划，以培训HBCU学生，以培训HBCU学生，以培训HBCU学生未来的研究人员。这些努力将共同提高网络安全，合作伙伴机构的研究能力以及HBCUS学生的研究和教育机会的研究，他们通常是计算中代表性不足的群体的成员。该合作伙伴关系将围绕五个种子研究项目组织，以最大程度地提高现有能力和协作。第一个将使用强化学习来通过当前的自主网络映射软件代理来改善目标选择。第二个涉及分析网络示踪数据，以更好地理解其映射路径能力的局限性，以便更好地检测和分类网络异常。第三个重点是开发，然后防止对计算机视觉算法的对抗性攻击，其中攻击者将视觉贴片添加到对象中以欺骗对象检测和分类工具。第四将分析现有的工具和算法，以生成“深击”视频，以开发几乎实时检测锻造视频的方法，并使用用于监视和身份验证任务的应用程序。第五将扩展概率顺序模型，以在物联网设备的背景下在网络堆栈的多个级别开发威胁探测器。除了这些特定的种子研究项目外，项目团队还将分析其活动，以开发基于证据的研究能力建设工作的最佳实践。这些努力将包括开发机制，以扩大当前的合作和培养资源，共享HBCU成员之间的专业知识，并举办一场年度研究会议，该会议允许来自现有和潜在合作伙伴HBCUS的教职员工和学生来展示其网络安全研究并建立与其他研究人员和资源建立联系。这些奖项反映了NSF的法定任务和审查的良好依据，这是通过评估良好的依据。