Project Details


Despite increasing awareness of the critical nature of cybersecurity, the cybersecurity workforce is currently insufficient to meet needs across the public, private, and academic sectors. The project will directly address the growing demand for cybersecurity professionals by increasing the number of effective cybersecurity learning materials available in a standardized and compatible format. These learning materials can then be widely adopted and used in training future members of the cybersecurity workforce. The proposed framework will also incentivize additional cybersecurity scholars to turn their research or teaching materials into case studies. These case studies will be attributable, which will expand societal and community impacts and also positively impact scholars' research reputations via citations and thus enhance their academic progression.

In this project, the team proposes to develop a simple yet flexible framework named SAGA (Security Arxiv-Github-kAggle), where scholars can easily create cybersecurity case studies related to artificial intelligence (AI) and machine learning (ML). For example, these case studies might illustrate the use of machine learning to detect malicious activities in social media or detecting spam/phishing emails using classification. Furthermore, by adopting the notion of 'citation' from the academic world and implementing it using three public platforms (arXiv, Github, Kaggle), the SAGA framework allows the developed case studies to be found easily and shared across the cybersecurity community and allows the authors of case studies to be appropriately recognized for their efforts. This attribution is intended to encourage scholars' participation in creating and sharing such cybersecurity case studies. Finally, the project proposes to evaluate the effectiveness of the developed cybersecurity case studies in improving students' learning of cybersecurity concepts and skills.

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.

Effective start/end date5/1/214/30/23


  • National Science Foundation: $312,568.00


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