| Classification of Encrypted Word Embeddings using Recurrent Neural Networks R Podschwadt, D Takabi PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020 | 26 | 2020 |
| A survey of deep learning architectures for privacy-preserving machine learning with fully homomorphic encryption R Podschwadt, D Takabi, P Hu, MH Rafiei, Z Cai IEEE Access 10, 117477-117500, 2022 | 23 | 2022 |
| On effectiveness of adversarial examples and defenses for malware classification R Podschwadt, H Takabi Security and Privacy in Communication Networks: 15th EAI International …, 2019 | 22* | 2019 |
| Privacy preserving neural network inference on encrypted data with GPUs D Takabi, R Podschwadt, J Druce, C Wu, K Procopio arXiv preprint arXiv:1911.11377, 2019 | 10 | 2019 |
| Non-interactive privacy preserving recurrent neural network prediction with homomorphic encryption R Podschwadt, D Takabi 2021 IEEE 14th International Conference on Cloud Computing (CLOUD), 65-70, 2021 | 9 | 2021 |
| NeuroCrypt: machine learning over encrypted distributed neuroimaging data N Senanayake, R Podschwadt, D Takabi, VD Calhoun, SM Plis Neuroinformatics 20 (1), 91-108, 2022 | 8 | 2022 |
| Sok: Privacy-preserving deep learning with homomorphic encryption R Podschwadt, D Takabi, P Hu arXiv preprint arXiv:2112.12855, 2021 | 4 | 2021 |
| Memory Efficient Privacy-Preserving Machine Learning Based on Homomorphic Encryption R Podschwadt, P Ghazvinian, M GhasemiGol, D Takabi International Conference on Applied Cryptography and Network Security, 313-339, 2024 | | 2024 |
| Privacy-Preserving Deep Learning with Homomorphic Encryption: Addressing Challenges Related to Usability, Memory, and Recurrent Neural Networks R Podschwadt | | 2023 |
| Privacy Preserving Recurrent Neural Network (RNN) Prediction using Homomorphic Encryption R Podschwadt, D Takabi The 42nd IEEE Symposium on Security and Privacy, 2021 | | 2021 |
| Adversarial Machine Learning Training Workshop R Podschwadt, H Takabi Annual Computer Security Applications Conference (ACSAC) 2019, 2019 | | 2019 |
| Adversarial Machine Learning Tutorial R Podschwadt, H Takabi Annual Computer Security Applications Conference (ACSAC) 2018, 2018 | | 2018 |
| Poster: Packing-aware Pruning for Efficient Private Inference based on Homomorphic Encryption P Ghazvinian, R Podschwadt, P Panzade, MH Rafiei, D Takabi Memory 303 (166), 166, 0 | | |
Daniel TakabiProfessor and Director of School of Cybersecurity, Old Dominion UniversityGeverifieerd e-mailadres voor odu.edu
