CICI: CE: Enhancing Cybersecurity for Broadening Data-Driven Research and Partnerships

CICI：CE：加强网络安全，扩大数据驱动的研究和合作伙伴关系

• 批准号: 1738981
• 负责人: Sonia Fahmy
• 金额: $ 84.15万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1738981&HistoricalAwards=false
• 关键词: CICI; CE; Enhancing; Cybersecurity; Broadening

As more disciplines leverage computational and data-driven modeling, the security of campus cyberinfrastructure is becoming increasingly important in order to protect intellectual property and secure a competitive advantage for researchers. Often, facilities and projects funded by industrial partners and US government agencies create new institutional requirements for information security and assurance. Designed for open science, the Purdue University campus cyberinfrastructure does not currently have infrastructure in place to support the wide variety of security requirements stemming from this growing volume of aerospace, defense, and industrial projects being conducted on campus. The rapid pace of expanding partnerships has outpaced the campus cybersecurity framework, limiting the opportunities for researchers and students to conduct research. This project brings together engineering and research teams to develop a cyber attack detection and response capability for the Purdue University campus research network.The project enhances the Purdue campus network to develop a security-assured research network infrastructure, and deploys novel adaptive monitoring tools as part of the campus cyberinfrastructure. Enhanced campus cyberinfrastructure empowers domain scientists to conduct research with heightened security requirements. The project also provides cybersecurity researchers with production network traffic data to develop and evaluate adaptive intrusion detection and response and flow-level anomaly detection. The proposed research will reduce the overhead of network security mechanisms, and improve their effectiveness, agility, and scalability. The project supports cybersecurity education and training by engaging students in deployment and operation of networking hardware and software. It provides students with a unique opportunity to apply their conceptual knowledge to practical situations and better prepares them to be part of the future workforce in cybersecurity. The highly interdisciplinary project team consists of security, networking and data science researchers, cybersecurity educators, campus Information Technology professionals and the engineering community.

随着越来越多的学科利用计算和数据驱动的建模，校园网络基础设施的安全性变得越来越重要，以保护知识产权并确保研究人员的竞争优势。通常，由工业合作伙伴和美国政府机构资助的设施和项目会为信息安全和保证提出新的制度要求。普渡大学校园网络基础设施专为开放科学而设计，目前还没有基础设施来支持校园内不断增长的航空航天，国防和工业项目所产生的各种安全要求。扩大合作伙伴关系的快速步伐已经超过了校园网络安全框架，限制了研究人员和学生进行研究的机会。该项目汇集了工程和研究团队，为普渡大学校园研究网络开发网络攻击检测和响应能力。该项目增强了普渡大学校园网络，以开发一个有安全保证的研究网络基础设施，并部署了新颖的自适应监控工具，作为校园网络基础设施的一部分。增强的校园网络基础设施使领域科学家能够进行具有更高安全要求的研究。该项目还为网络安全研究人员提供生产网络流量数据，以开发和评估自适应入侵检测和响应以及流级异常检测。该研究将减少网络安全机制的开销，提高其有效性、灵活性和可扩展性。该项目通过让学生参与网络硬件和软件的部署和操作来支持网络安全教育和培训。它为学生提供了一个独特的机会，将他们的概念知识应用于实际情况，并更好地准备他们成为未来网络安全劳动力的一部分。高度跨学科的项目团队由安全，网络和数据科学研究人员，网络安全教育工作者，校园信息技术专业人员和工程社区组成。

项目成果

PULSAR: Deploying Network Monitoring and Intrusion Detection for the Science DMZ

• DOI: 10.1145/3332186.3333058
• 发表时间: 2019-07
• 期刊: Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning)
• 作者: Shivam Trivedi;Lauren Featherstun;Nathan DeMien;Callum Gunlach;Sagar Narayan;J. Sharp;Brian Werts;Lipu Wu;Carolyn Ellis;Lev Gorenstein;E. Gough;Alex Younts;Xiao Zhu

Mentoring Undergraduates into Cyber-Facilitator Roles

指导本科生担任网络促进者角色

• DOI: 10.1145/3219104.3219138
• 发表时间: 2018
• 期刊: Proceedings of the Practice and Experience on Advanced Research Computing
• 作者: Harrell, Stephen Lien;Brazil, Marisa;Younts, Alex;Dietz, Daniel T.;Smith, Preston;Gough, Erik;Zhu, Xiao;Andino, Gladys K.
• 通讯作者: Andino, Gladys K.

Experience: towards automated customer issue resolution in cellular networks

经验：在蜂窝网络中实现自动化客户问题解决

• DOI: 10.1145/3372224.3419203
• 发表时间: 2020
• 期刊: United Kingdom
• 作者: Sheoran, Amit;Fahmy, Sonia;Osinski, Matthew;Peng, Chunyi;Ribeiro, Bruno;Wang, Jia
• 通讯作者: Wang, Jia

Data-driven resource flexing for network functions visualization

• DOI: 10.1145/3230718.3230725
• 发表时间: 2018-07
• 期刊: Proceedings of the 2018 Symposium on Architectures for Networking and Communications Systems
• 作者: Lianjie Cao;S. Fahmy;P. Sharma;Shandian Zhe

Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations

• DOI: 10.1609/aaai.v34i04.5806
• 发表时间: 2020-02
• 作者: Jianfei Gao;Mohamed Zahran;Amit Sheoran;S. Fahmy;Bruno Ribeiro