Scholarly and Creative Works
2025
- Holiday, G., & Klepetko, R. S. (2025). Interpreting CNN in Cybersecurity: Process-Level Attribution via Benign-Replacement Occlusion (BRO). IEEE. https://doi.org/10.1109/ICCST63435.2025.11295312
2023
- Klepetko, R. S., & Krishnan, R. (2023). Micam: Visualizing Feature Extraction of Nonnatural Data. In 4th International Conference on Machine Learning and Soft Computing (pp. 01–19). https://doi.org/10.5121/csit.2023.130201
2022
- Klepetko, R. S., & Krishnan, R. (2022). Visualizing Convolutional Neural Network Models’ Sensitivity to Nonnatural Data Order. Information Systems Frontiers, 25(2), 613–638. https://doi.org/10.1007/s10796-022-10330-0
2021
- Klepetko, R. S., & Krishnan, R. (2021). Analyzing CNN Models’ Sensitivity to the Ordering of Non-natural Data. In R. Krishnan, H. R. Rao, S. K. Sahay, S. Samtani, & Z. Zhao (Eds.), Secure Knowledge Management In The Artificial Intelligence Era - 9th International Conference, SKM 2021, San Antonio, TX, USA, October 8-9, 2021, Proceedings (Vol. 1549, pp. 130–148). Springer. https://doi.org/10.1007/978-3-030-97532-6\_8
2019
- Klepetko, R. S., & Krishnan, R. (2019). Analyzing CNN Model Performance Sensitivity to the Ordering of Non-Natural Data. In 2019 4th International Conference on Computing, Communications and Security (ICCCS), Rome, Italy, October 10-12, 2019 (pp. 1--8). IEEE. https://doi.org/10.1109/CCCS.2019.8888041