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Collaborative Research: EAGER: SaTC-EDU: Learning Platform and Education Curriculum for Artificial Intelligence-Driven Socially-Relevant Cybersecurity

Collaborative Research: EAGER: SaTC-EDU: Learning Platform and Education Curriculum for Artificial Intelligence-Driven Socially-Relevant Cybersecurity
合作研究:EAGER:SaTC-EDU:人工智能驱动的社会相关网络安全的学习平台和教育课程
批准号:
2114982
负责人:
Hongxin Hu
金额:
$7.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-06-01 至 2024-09-30

项目摘要

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中文摘要
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英文摘要
With the rise of social media, cyberharassment has been identified as a critical social-cybersecurity problem. Artificial intelligence (AI) has immense potential to solve this problem by automating detection. Nevertheless, while AI can be a useful tool in the fight against cyberharassment, it is vulnerable to adversarial attacks. In addition, AI-driven cyberharrassment detection models may have embedded social problems, such as fairness and ethics. To advance AI-cybersecurity education, this project will develop curricular modules and hands-on labs. These modules will be based on cutting-edge research on AI-driven cyberharassment detection, related attacks against the AI models, and social issues in AI models for cyberharassment detection. This project will benefit both computer science (CS) and non-CS (e.g., social science) students due to the highly interdisciplinary nature of AI-driven cyberharassment detection . The pervasiveness and severity of cyberharassment in the era of social media makes this project ideal for motivating and educating students about the mutual needs and benefits of AI and social-cybersecurity. This project will attract students with diverse backgrounds (specifically from underrepresented groups) into the AI-cybersecurity field and increase general awareness of cybersecurity and AI. The goal of this project is to transform recent research outcomes in emerging social-cybersecurity into an educational format. This project will develop hands-on labs that cover different dimensions of AI-driven social-cybersecurity and demonstrate the interplay between AI and cybersecurity. The hands-on labs will be integrated into a cloud-based open learning platform, which contains 1) the project team’s homegrown and classic AI-driven cyberharassment detection algorithms; 2) adversarial attacks against these AI algorithms and defenses; and 3) social issues and bias mitigation in AI models. The proposed learning platform will provide students with an in-depth understanding of social-cybersecurity problems and AI techniques through their own experimentation. The project team will develop course materials for both CS and non-CS students and will also develop curriculum materials and organize summer camps for high school students to increase their cybersecurity awareness and interest in the related fields. The cloud-based open labs and learning platform designed in this project will be easily accessed by faculty from other universities. This project is supported by a special initiative of the Secure and Trustworthy Cyberspace (SaTC) program to foster new, previously unexplored, collaborations between the fields of cybersecurity, artificial intelligence, and 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.
期刊论文(8)
专著(0)
科研奖励(0)
会议论文
DOI: --
发表时间: 2021-06
期刊: ArXiv
影响因子: --
作者: [Dian Chen;Hongxin Hu;Qian Wang;Yinli Li;Cong Wang;Chao Shen;Qi Li]
通讯作者: Dian Chen;Hongxin Hu;Qian Wang;Yinli Li;Cong Wang;Chao Shen;Qi Li
Understanding and Measuring Robustness of Vision and Language Multimodal Models
理解和测量视觉和语言多模态模型的鲁棒性
DOI: --
发表时间: 2023
期刊: Proceedings of the International Conference on Secure Knowledge Management (SKM 2023
影响因子: --
作者: [Vishwamitra, Nishant, Guo, Keyan, Hu, Hongxin, Zhao, Ziming, Cheng, Long, Luo, Feng]
通讯作者: Luo, Feng
BYOZ: Protecting BYOD Through Zero Trust Network Security
BYOZ:通过零信任网络安全保护 BYOD
DOI: --
发表时间: 2022
期刊: and Storage
影响因子: --
作者: [Anderson, John, Huang, Qiqing, Cheng, Long, Hu, Hongxin]
通讯作者: Hu, Hongxin
DOI: --
发表时间: 2023
期刊: Proceedings of the 36th Annual Computer Security Applications Conference
影响因子: --
作者: [Feng Wei;Hongda Li;Ziming Zhao;Hongxin Hu]
通讯作者: Feng Wei;Hongda Li;Ziming Zhao;Hongxin Hu
8
    Collaborative Research: SAI-R: Integrative Cyberinfrastructure for Enhancing and Accelerating Online Abuse Research
    • 批准号:
      2228617
    • 项目类别:
      Standard Grant
    • 资助金额:
      $37.5万
    • 财政年份:
      2022
    • 负责人:
      Hongxin Hu
    • 依托单位:
    SDI-CSCS: Collaborative Research: S2OS: Enabling Infrastructure-Wide Programmable Security with SDI
    • 批准号:
      2128107
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $40.0万
    • 财政年份:
      2021
    • 负责人:
      Hongxin Hu
    • 依托单位:
    CAREER: Towards Elastic Security with Safe and Efficient Network Security Function Virtualization
    • 批准号:
      2129164
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $50.0万
    • 财政年份:
      2021
    • 负责人:
      Hongxin Hu
    • 依托单位:
    Collaborative Research: CICI: Secure and Resilient Architecture: SciGuard: Building a Security Architecture for Science DMZ Based on SDN and NFV Technologies
    • 批准号:
      2128607
    • 项目类别:
      Standard Grant
    • 资助金额:
      $49.98万
    • 财政年份:
      2021
    • 负责人:
      Hongxin Hu
    • 依托单位:
    国内基金
    海外基金
    Research on Quantum Field Theory without a Lagrangian Description
    • 批准号:
      24ZR1403900
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      SATOSHI NAWATA
    • 依托单位:
    Cell Research
    Cell Research
    Cell Research (细胞研究)