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

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.