SaTC: EDU: Secure and Private Artificial Intelligence
SaTC:EDU:安全且私密的人工智能
基本信息
- 批准号:2054968
- 负责人:
- 金额:$ 39.97万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-06-15 至 2024-02-29
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
As artificial intelligence (AI) is incorporated into more systems, there are growing cybersecurity concerns related to privacy protection as well as a need for highly trained professionals who can develop and deploy trustworthy AI systems. The goal of this project is to develop instructional materials that expose students to privacy issues inherent in AI systems through real-world examples. The project will have a direct and long-term impact by addressing the growing national need for highly trained professionals capable of taking a holistic approach to solving real world problems in complex AI systems. In addition, the project will benefit numerous students from underrepresented minority groups and improve diversity of the workforce. Georgia State University is a minority-serving institution and has strong connections with Historically Black Colleges and Universities (HBCUs) in Metro Atlanta and the wider region. The project will disseminate the developed materials through training workshops for the educational community and therefore promote adoption of training modules addressing privacy and AI.The interdisciplinary project team will develop a new course, “Private AI”, which will include instructional modules and hands-on labs that employ state-of-the-art private AI techniques addressing different privacy challenges of AI systems. These instructional modules will be designed according to learning science principles, specifically the principles of problem-centered instruction (PCI). The modules will be based on real-world systems and are designed to cover fundamental privacy principles in AI systems and practical skills systematically. The learning objectives of the interactive curricular activities are for students to (i) understand fundamental concepts and principles of private AI; (ii) understand privacy attacks and defenses, different privacy-preserving techniques, and the pros and cons of each approach; and (iii) gain knowledge and skills in the development and deployment of private AI systems. The deliverables also include manuals to help instructors integrate the modules into their curricula and guidelines on implementing PCI activities in the classroom since many instructors are not experts in instructional sciences. In order to simplify integration and encourage adoption, the modules and the labs will be based on open-source software and tools that are free to use for educational purposes. The modules will also be distributed via free cloud platforms. This project is supported by the Secure and Trustworthy Cyberspace (SaTC) program, which funds proposals that address cybersecurity and privacy, and in this case specifically cybersecurity education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.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.
随着人工智能(AI)被纳入更多的系统中,与隐私保护相关的网络安全问题越来越多,并且需要训练有素的专业人员来开发和部署值得信赖的AI系统。该项目的目标是开发教学材料,通过真实世界的例子让学生了解人工智能系统中固有的隐私问题。该项目将产生直接和长期的影响,解决国家对训练有素的专业人员日益增长的需求,这些专业人员能够采取全面的方法来解决复杂人工智能系统中的真实的世界问题。此外,该项目还将使代表性不足的少数群体的许多学生受益,并提高劳动力的多样性。格鲁吉亚州立大学是一所为少数民族服务的机构,与亚特兰大市区和更广泛地区的历史黑人学院和大学(HBCU)有着密切的联系。该项目将通过面向教育界的培训研讨会传播开发的材料,从而促进采用针对隐私和人工智能的培训模块。跨学科项目团队将开发一门新课程“私人人工智能”,其中将包括教学模块和实践实验室,采用最先进的私人人工智能技术来解决人工智能系统的不同隐私挑战。这些教学模块将根据学习科学的原则,特别是以问题为中心的教学(PCI)的原则设计。这些模块将基于真实世界的系统,旨在系统地涵盖人工智能系统中的基本隐私原则和实用技能。互动课程活动的学习目标是让学生(i)了解私人AI的基本概念和原则;(ii)了解隐私攻击和防御,不同的隐私保护技术以及每种方法的优缺点;(iii)获得开发和部署私人AI系统的知识和技能。交付的成果还包括帮助教员将这些单元纳入其课程的手册和关于在课堂上实施项目关注活动的准则,因为许多教员不是教学科学方面的专家。为了简化集成并鼓励采用,模块和实验室将基于免费用于教育目的的开源软件和工具。这些模块也将通过免费的云平台分发。该项目得到了安全和值得信赖的网络空间(SaTC)计划的支持,该计划为解决网络安全和隐私问题的提案提供资金,在这种情况下,特别是网络安全教育。SATC计划与联邦网络安全研究和发展战略计划和国家隐私研究战略保持一致,以保护和维护网络系统日益增长的社会和经济效益,同时确保安全和隐私。该奖项反映了NSF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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Daniel Takabi其他文献
A Hybrid Policy Engineering Approach for Attribute-Based Access Control (ABAC)
基于属性的访问控制 (ABAC) 的混合策略工程方法
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Manar Alohaly;Daniel Takabi - 通讯作者:
Daniel Takabi
Privacy preserving Neural Network Inference on Encrypted Data with GPUs
使用 GPU 对加密数据进行隐私保护神经网络推理
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Daniel Takabi;Robert Podschwadt;Jeff Druce;Curt Wu;Kevin Procopio - 通讯作者:
Kevin Procopio
Poster: Packing-aware Pruning for Efficient Private Inference based on Homomorphic Encryption
海报:基于同态加密的高效私有推理的打包感知剪枝
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Parsa Ghazvinian;Robert Podschwadt;Prajwal Panzade;M. Rafiei;Daniel Takabi - 通讯作者:
Daniel Takabi
Daniel Takabi的其他文献
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{{ truncateString('Daniel Takabi', 18)}}的其他基金
SaTC: EDU: Secure and Private Artificial Intelligence
SaTC:EDU:安全且私密的人工智能
- 批准号:
2413856 - 财政年份:2023
- 资助金额:
$ 39.97万 - 项目类别:
Continuing Grant
SaTC: CORE: Small: An Attribute-based Insider Threat Mitigation Framework
SaTC:核心:小型:基于属性的内部威胁缓解框架
- 批准号:
2406038 - 财政年份:2023
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
Building Cybersecurity Analytics Capacity in Big Data Era: Developing Hands-on Labs for Integrating Data Science into Cybersecurity Curriculum
建设大数据时代的网络安全分析能力:开发将数据科学融入网络安全课程的实践实验室
- 批准号:
2415022 - 财政年份:2023
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
CyberTraining: Implementation: Small: Building Future Research Workforce in Trustworthy Artificial Intelligence (AI)
网络培训:实施:小型:建立可信赖人工智能 (AI) 领域的未来研究队伍
- 批准号:
2413654 - 财政年份:2023
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
CyberTraining: Implementation: Small: Building Future Research Workforce in Trustworthy Artificial Intelligence (AI)
网络培训:实施:小型:建立可信赖人工智能 (AI) 领域的未来研究队伍
- 批准号:
2118083 - 财政年份:2021
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
Building Cybersecurity Analytics Capacity in Big Data Era: Developing Hands-on Labs for Integrating Data Science into Cybersecurity Curriculum
建设大数据时代的网络安全分析能力:开发将数据科学融入网络安全课程的实践实验室
- 批准号:
2020636 - 财政年份:2020
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
NSF Student Travel Grant for 2019 ACM Conference on Computer and Communications Security (ACM CCS)
2019 年 ACM 计算机和通信安全会议 (ACM CCS) 的 NSF 学生旅行补助金
- 批准号:
1932911 - 财政年份:2019
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
NSF Student Travel Grant for 2019 ACM Conference on Computer and Communications Security (ACM CCS)
2019 年 ACM 计算机和通信安全会议 (ACM CCS) 的 NSF 学生旅行补助金
- 批准号:
2001093 - 财政年份:2019
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
SaTC: CORE: Small: An Attribute-based Insider Threat Mitigation Framework
SaTC:核心:小型:基于属性的内部威胁缓解框架
- 批准号:
2006329 - 财政年份:2019
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
NSF Student Travel Grant for 2018 ACM Conference on Computer and Communications Security (ACM CCS)
2018 年 ACM 计算机和通信安全会议 (ACM CCS) 的 NSF 学生旅行补助金
- 批准号:
1837755 - 财政年份:2018
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
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相似海外基金
SaTC: EDU: Secure and Private Artificial Intelligence
SaTC:EDU:安全且私密的人工智能
- 批准号:
2413856 - 财政年份:2023
- 资助金额:
$ 39.97万 - 项目类别:
Continuing Grant
Collaborative Research: EAGER: SaTC-EDU: Secure and Privacy-Preserving Adaptive Artificial Intelligence Curriculum Development for Cybersecurity
合作研究:EAGER:SaTC-EDU:安全和隐私保护的网络安全自适应人工智能课程开发
- 批准号:
2335624 - 财政年份:2023
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
Collaborative Research: EAGER: SaTC-EDU: Secure and Privacy-Preserving Adaptive Artificial Intelligence Curriculum Development for Cybersecurity
合作研究:EAGER:SaTC-EDU:安全和隐私保护的网络安全自适应人工智能课程开发
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2039408 - 财政年份:2020
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
Collaborative Research: EAGER: SaTC-EDU: Secure and Privacy-Preserving Adaptive Artificial Intelligence Curriculum Development for Cybersecurity
合作研究:EAGER:SaTC-EDU:安全和隐私保护的网络安全自适应人工智能课程开发
- 批准号:
2039434 - 财政年份:2020
- 资助金额:
$ 39.97万 - 项目类别:
Standard Grant
Collaborative Research: EAGER: SaTC-EDU: Secure and Privacy-Preserving Adaptive Artificial Intelligence Curriculum Development for Cybersecurity
合作研究:EAGER:SaTC-EDU:安全和隐私保护的网络安全自适应人工智能课程开发
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2039542 - 财政年份:2020
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1931800 - 财政年份:2020
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SaTc: EDU: Collaborative: An Assessment Driven Approach to Self-Directed Learning in Secure Programming (SecTutor)
SaTc:EDU:协作:安全编程中自我导向学习的评估驱动方法(SecTutor)
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1934269 - 财政年份:2019
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- 批准号:
1934285 - 财政年份:2019
- 资助金额:
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1523041 - 财政年份:2015
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