T3-CIDERS: Fostering a Community of Practice in CI- and Data-Enabled Cybersecurity Research Through a Train-the-Trainer Program
We present a training program named T³-CIDERS, the Train- The-Trainer approach to fostering cyberinfrastructure (CI)- and Data-Enabled Research in CyberSecurity. T³-CIDERS is a train-the-trainer program for advanced cyberinfrastructure (CI) skills that is designed to be synergistic with research, teaching, and learning activities in cybersecurity and cyber-related disciplines. The participants, termed 'future trainers' (FTs), are trained in effective instructional design and CI hands-on materials from DeapSECURE, developed in a previous CyberTraining program. T³-CIDERS aims to enhance cybersecurity research and education through broader adoption of advanced CI techniques such as artificial intelligence, big data, parallel programming, and platforms like high-performance computing (HPC) systems. T³-CIDERS includes pre-training, a weeklong summer institute, ongoing learning engagements, and local training activities. The FTs conduct local training tailored to the needs at their respective home institutions. They will also develop a new CI training module (called 'Module X') based on the observed common needs in the cybersecurity research community. Community building is integral to T³-CIDERS as its overarching goal. The first cohort of FTs who took the 2024 summer institute comprises faculty members, researchers, and students representing multiple states.
Authors
- Peng Jiang (ORCID: https://orcid.org/0000-0002-4218-0092)
- Mohan Yang (ORCID: https://orcid.org/0000-0003-0856-0814)
- Wirawan Purwanto (ORCID: https://orcid.org/0000-0002-2124-4552)
- Masha Sosonkina (ORCID: https://orcid.org/0009-0005-0223-397X)
- Hongyi Wu (ORCID: https://orcid.org/0000-0002-6112-9313)
Publication Details
- Journal
- The Journal of Computational Science Education
- Published
- 2025-03-01
- DOI
- https://doi.org/10.22369/issn.2153-4136/16/1/4
- Primary Topic
- Information and Cyber Security
- Type
- article
- Field-Weighted Citation Impact
- 0.00