Collaborative Research: CyberTraining: Pilot: Operationalizing AI/Machine Learning for Cybersecurity Training

合作研究：网络培训：试点：将人工智能/机器学习应用于网络安全培训

• 批准号: 2229976
• 负责人: Jiawei Yuan
• 金额: $ 14万
• 依托单位: University of Massachusetts, Dartmouth
• 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
• 起止时间: 2023-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2229976&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Pilot; Operationalizing

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 with a security mindset are rarely covered in the typical curriculum. To fill this gap, this project intends to develop hands-on training materials and provide mentored training for trainees in engineering and science-related disciplines. By transforming and integrating training materials into the curriculum, this project benefits the potential cyberinfrastructure professionals in the community at large. This project has the potential to develop the research workforce in operating AI cyberinfrastructure with a security mindset to meet national and economic priorities. This project’s goal is broadening adoption of advanced cyberinfrastructure. 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 for different education and training environments. The project broadens 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 dissemination through publications and social media, the outcomes from this project have the potential to benefit the greater cyberinfrastructure community and beyond. 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.

人工智能和网络安全之间的相互作用为人工智能的网络安全以及人工智能的网络安全带来了新的机遇和挑战，然而，典型课程中很少涵盖具有安全思维的人工智能网络基础设施的操作和配置。旨在开发实践培训材料，并为工程和科学相关学科的学员提供指导培训。通过将培训材料转化并整合到课程中，该项目使整个社区中潜在的网络基础设施专业人员受益。开展研究该项目的目标是扩大先进网络基础设施的采用，以安全的心态操作人工智能网络基础设施。该项目开发了一种整体的网络培训技术方法：识别、应用和评估与人工智能密切相关的技术。该项目旨在开发一个基于 Docker 的培训平台，该平台可以模拟和预配置各种场景，以支持网络安全背景下的实际 AI 网络基础设施操作。项目（探索性、核心和高级）被设计并集成到该平台中，以帮助研究人员和教育工作者针对不同的教育和培训环境进行定制和开发。该项目扩大了先进人工智能网络基础设施的访问和采用，同时将网络基础设施技能与安全思维相结合。除了通过出版物和社交媒体传播之外，该项目的成果还有可能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 OAC 共同资助。 Cyber​​Corps 计划。这反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Hybrid Delay-aware Approach Towards UAV Flight Data Anomaly Detection

• DOI: 10.1109/icnc57223.2023.10074138
• 发表时间: 2023-02
• 期刊: 2023 International Conference on Computing, Networking and Communications (ICNC)
• 作者: Mengjie Jia;A. Raja;Jiawei Yuan

Towards the Security of AI-Enabled UAV Anomaly Detection

• DOI: 10.1109/icc45041.2023.10279224
• 发表时间: 2023-05
• 期刊: ICC 2023 - IEEE International Conference on Communications
• 作者: A. Raja;Mengjie Jia;Jiawei Yuan