CC* Integration: NetBASILISK: NETwork Border At Scale Integrating and Leveraging Individual Security Components

NetBASILISK（网络边界大规模集成和利用个人安全组件）项目使密歇根大学的研究人员和网络工程师能够引入下一个级别的安全和隐私保护，以应对大量生成的研究数据。随着攻击者开发出更复杂的工具来获取学生和教师的私人数据、机构财务信息以及专有的、通常是分类的研究信息，信息技术人员必须检测并阻止这些攻击。通过观察网络流量的模式，NetBASILISK将在对网络流量的速度或容量影响最小的情况下实现这些目标。目前的威胁预防系统无法以可承受的成本适应不断增长的研究数据量。密歇根大学的解决方案是一个结合了开源和专有组件的新框架，显著提高了系统性能和检测和预防机构数据威胁的准确性。NetBASILISK包括强大的负载均衡威胁防护机制、数据过滤工具和威胁检测技术。NetBASILISK将创建一个安全的网络边界，同时促进科学研究，如低温电子显微镜，大型强子对撞机粒子研究和非扭曲的互联网测量，以及实现创新的网络增强，如绕过网络审查的技术。NetBASILISK将用于为大学设计先进的网络安全设备，以适应数据密集型科学的网络流量需求。该项目的经验教训和技术改进将与大学网络社区以及商业合作伙伴共享。科学界将了解从用于边境安全的新设计模式中吸取的经验教训。该项目的科学驱动因素，包括低温电子显微镜、网络和物理学的进步，将提供广泛的、有影响力的好处。项目资金也将用于支持教师、研究生和博士后研究员。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。

The NetBASILISK (NETwork Border At Scale Integrating and Leveraging Individual Security Components) project enables researchers and network engineers at the University of Michigan to introduce the next level of security and privacy protection scaled to the vast volume of generated research data. As attackers develop more sophisticated tools to acquire student and faculty private data, institutional financial information, and proprietary, often classified, research information, it is imperative for information technology staff to detect and stop these attacks. By observing patterns of network traffic, NetBASILISK will accomplish these goals with a minimal impact on the speed or volume of network traffic.Current threat prevention systems do not scale to the growing volume of research data at an affordable cost. The University of Michigan solution, a novel framework combining open source and proprietary components, significantly improves system performance and accuracy in detecting and preventing threats to institutional data. NetBASILISK comprises powerful load balancing threat prevention mechanisms, data filtering tools, and threat detection technology. NetBASILISK will create a secure network perimeter while facilitating science such as cryo-electron microscopy, Large Hadron Collider particle research, and non-distorted Internet measurement, as well as enabling innovative network enhancements such as technologies to circumvent web censorship.NetBASILISK will be used to inform the design of advanced network security devices for universities that scale to accommodate the network traffic requirements of data intensive science. Lessons learned and technology enhancements discovered by the project will be shared with the university networking community, as well as commercial partners. The science community will be informed of lessons learned from new design patterns employed for border security. The science drivers of the project, including advances in cryo-electron microscopy, networking, and physics will provide broad, impactful benefits. Project funding will also be used to support faculty, graduate students, and a postdoctoral researcher.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.