Collaborative Research: CyberTraining: Pilot: Operationalizing AI/Machine Learning for Cybersecurity Training
Collaborative Research: CyberTraining: Pilot: Operationalizing AI/Machine Learning for Cybersecurity Training
批准号:
2309760
负责人:
Houbing Song
金额:
$16.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-01-01 至 2024-12-31
中文摘要
人工智能与网络安全的相互作用为人工智能网络安全以及人工智能网络安全带来了新的机遇和挑战。然而,典型的人工智能课程很少涉及具有安全思维的人工智能网络基础设施(CI)的运营和配置。为了填补这一空白,该项目打算开发实践培训材料,并为当前和未来的工程和科学相关学科的研究人员提供指导培训。通过将培训材料转换并整合到课程课程中,该项目旨在培训整个CI社区中潜在的网络基础设施专业人员,使其能够与网络安全一起处理人工智能。该项目有潜力培养具有安全思维的人工智能网络基础设施运营研究人员,以满足国家和经济需求以及人工智能发展的优先事项。该项目的目标是通过培训扩大先进网络基础设施的采用。该项目为网络培训开发了一种全面的技术方法:识别、应用和评估与明确定义的操作网络安全挑战密不可分的人工智能技术。该项目旨在开发一个基于docker的培训平台,模拟和预配置各种场景,以支持在网络安全背景下的人工智能网络基础设施操作。平台设计并集成了探索性、核心性和高级性三个层次的项目,帮助科研人员和教育工作者定制和开发不同的教育培训环境。该项目使先进的人工智能网络基础设施的访问和采用民主化,同时将网络基础设施技能与安全思维相结合,以促进跨学科和机构间的研究合作。除了通过出版物和社交媒体进行传播外,该项目的成果还有可能通过培训和分享“网络安全中的人工智能”课程课程,使更大的网络基础设施社区及其他领域受益。该项目由OAC和赛博军团计划共同资助。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。
英文摘要
The interplay between AI and cybersecurity introduces new opportunities and challenges in the cybersecurity of AI as well as AI for cybersecurity. However, operations and configurations of AI cyberinfrastructure (CI) with a security mindset are rarely covered in the typical AI curriculum. To fill this gap, this project intends to develop hands-on training materials and provide mentored training for current and future research workforce in engineering and science-related disciplines. By transforming and integrating training materials into a course curriculum, this project aims to train potential cyberinfrastructure professionals in the CI community at large to handle AI with and for cybersecurity. This project has the potential to develop the research workforce in operating AI cyberinfrastructure with a security mindset to meet the national and economical needs and priorities of CI advancement. This project’s goal is to broaden the adoption of advanced cyberinfrastructure through training. This project develops a holistic technical approach for cybertraining: to identify, apply, and evaluate AI techniques which are inextricably related to well-defined operational cybersecurity challenges. The project intends to develop a Docker-based training platform that simulates and pre-configures a variety of scenarios to support hands-on AI cyberinfrastructure operations in the context of cybersecurity. Three levels of projects (exploratory, core, and advanced) are designed and integrated into the platform to help researchers and educators customize and develop into different education and training environments. The project democratizes the access and adoption of advanced AI cyberinfrastructure, while integrating cyberinfrastructure skills with the security mindset to foster inter-disciplinary and inter-institutional research collaborations. In addition to the dissemination through publications and social media, the outcomes from this project have the potential to benefit the greater cyberinfrastructure community and beyond, through the training and the sharing of the "AI for and with cybersecurity" course curriculum. This project is jointly funded by OAC and the CyberCorps program.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.
期刊论文(5)
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DOI:
10.1109/iri58017.2023.00048
发表时间:
2023-07
期刊:
2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI)
影响因子:
--
作者:
[Ke-ke Feng;Dahai Liu;Yongxin Liu;Hong Liu;H. Song]
通讯作者:
Ke-ke Feng;Dahai Liu;Yongxin Liu;Hong Liu;H. Song
DOI:
10.1145/3606042.3616460
发表时间:
2023-10
期刊:
Proceedings of the 2023 Workshop on Advanced Multimedia Computing for Smart Manufacturing and Engineering
影响因子:
--
作者:
[H. Song]
通讯作者:
H. Song
DOI:
10.1109/tai.2024.3351798
发表时间:
2024-01
期刊:
ArXiv
影响因子:
--
作者:
[Justus Renkhoff;Ke Feng;Marc Meier-Doernberg;Alvaro Velasquez;Houbing Herbert Song]
通讯作者:
Justus Renkhoff;Ke Feng;Marc Meier-Doernberg;Alvaro Velasquez;Houbing Herbert Song
DOI:
10.1109/tai.2023.3311428
发表时间:
2023-09
期刊:
IEEE Transactions on Artificial Intelligence
影响因子:
--
作者:
[Kamal Acharya;Waleed Raza;Carlos Dourado;Alvaro Velasquez;Houbing Song]
通讯作者:
Kamal Acharya;Waleed Raza;Carlos Dourado;Alvaro Velasquez;Houbing Song
DOI:
10.1109/fuzz52849.2023.10309766
发表时间:
2023-03
期刊:
2023 IEEE International Conference on Fuzzy Systems (FUZZ)
影响因子:
--
作者:
[Wen-Xi Tan;Justus Renkhoff;Alvaro Velasquez;Ziyu Wang;Lu Li;Jian Wang;Shuteng Niu;Fan Yang;Yongxin Liu;H. Song]
通讯作者:
Wen-Xi Tan;Justus Renkhoff;Alvaro Velasquez;Ziyu Wang;Lu Li;Jian Wang;Shuteng Niu;Fan Yang;Yongxin Liu;H. Song
Collaborative Research: CyberTraining: Pilot: Operationalizing AI/Machine Learning for Cybersecurity Training
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批准号:2229975
-
项目类别:Standard Grant
-
资助金额:$16.0万
-
财政年份:2023
-
负责人:Houbing Song
-
依托单位:
SaTC: EDU: Collaborative: Bolstering UAV Cybersecurity Education through Curriculum Development with Hands-on Laboratory Framework
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批准号:2317117
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项目类别:Standard Grant
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资助金额:$32.0万
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财政年份:2023
-
负责人:Houbing Song
-
依托单位:
SaTC: EDU: Collaborative: Bolstering UAV Cybersecurity Education through Curriculum Development with Hands-on Laboratory Framework
-
批准号:1956193
-
项目类别:Standard Grant
-
资助金额:$32.0万
-
财政年份:2020
-
负责人:Houbing Song
-
依托单位:
国内基金
海外基金
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