| 2025 | TrustCom | Fairness-Constrained Optimization Attack in Federated Learning. | Harsh Kasyap, Minghong Fang, Zhuqing Liu, Carsten Maple, Somanath Tripathy |
| 2025 | TrustCom | An Improved Vector Commitment Construction with Applications to Signatures. | Yalan Wang, Bryan Kumara, Harsh Kasyap, Liqun Chen, Sumanta Sarkar, Christopher J. P. Newton, Carsten Maple, Ugur-Ilker Atmaca |
| 2024 | ECAI | Mitigating Bias: Model Pruning for Enhanced Model Fairness and Efficiency. | Harsh Kasyap, Ugur-Ilker Atmaca, Michela Iezzi, Toby Walsh, Carsten Maple |
| 2023 | TrustCom | HDFL: Private and Robust Federated Learning using Hyperdimensional Computing. | Harsh Kasyap, Somanath Tripathy, Mauro Conti |
| 2022 | CISS | Hidden Vulnerabilities in Cosine Similarity based Poisoning Defense. | Harsh Kasyap, Somanath Tripathy |
| 2022 | ICISS | MILSA: Model Interpretation Based Label Sniffing Attack in Federated Learning. | Debasmita Manna, Harsh Kasyap, Somanath Tripathy |
| 2021 | ICDCIT | DNet: An Efficient Privacy-Preserving Distributed Learning Framework for Healthcare Systems. | Parth Parag Kulkarni, Harsh Kasyap, Somanath Tripathy |
| 2021 | ICICS | Moat: Model Agnostic Defense against Targeted Poisoning Attacks in Federated Learning. | Arpan Manna, Harsh Kasyap, Somanath Tripathy |