| Mini-me, you complete me! data-driven drone security via dnn-based approximate computing A Ding, P Murthy, L Garcia, P Sun, M Chan, S Zonouz Proceedings of the 24th International Symposium on Research in Attacks …, 2021 | 18 | 2021 |
| Reverse engineering and retrofitting robotic aerial vehicle control firmware using dispatch T Kim, A Ding, S Etigowni, P Sun, J Chen, L Garcia, S Zonouz, D Xu, ... Proceedings of the 20th Annual International Conference on Mobile Systems …, 2022 | 11 | 2022 |
| FADE: enabling large-scale federated adversarial training on resource-constrained edge devices M Tang, J Zhang, M Ma, L DiValentin, A Ding, A Hassanzadeh, H Li, ... | 5 | 2022 |
| Privacy-preserving collaborative machine learning training using distributed executable file packages in an untrusted environment A Hassanzadeh, NH Liberman, A Ding, MB Salem US Patent App. 17/356,447, 2022 | 3 | 2022 |
| Get Your Cyber-Physical Tests Done! Data-Driven Vulnerability Assessment of Robotic Aerial Vehicles A Ding, M Chan, A Hass, NO Tippenhauer, S Ma, S Zonouz 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems …, 2023 | 2* | 2023 |
| Privacy-preserving machine learning training based on homomorphic encryption using executable file packages in an untrusted environment A Hassanzadeh, NH Liberman, A Ding, MB Salem US Patent App. 17/383,314, 2023 | 2 | 2023 |
| Privacy preserving cooperative learning in untrusted environments A Ding, A Hassanzadeh US Patent App. 17/695,820, 2022 | 2 | 2022 |
| Trustworthy cyber-physical systems via physics-aware and AI-powered security A Ding Rutgers The State University of New Jersey, School of Graduate Studies, 2022 | 2 | 2022 |
| MODELGUARD: Information-Theoretic Defense Against Model Extraction Attacks M Tang, A Dai, L DiValentin, A Ding, A Hass, NZ Gong, Y Chen | 2 | |
| Resource-Aware DNN Partitioning for Privacy-Sensitive Edge-Cloud Systems A Ding, A Hass, M Chan, N Sehatbakhsh, S Zonouz International Conference on Neural Information Processing, 188-201, 2023 | 1 | 2023 |
| FADE: Enabling Federated Adversarial Training on Heterogeneous Resource-Constrained Edge Devices M Tang, J Zhang, M Ma, L DiValentin, A Ding, A Hassanzadeh, H Li, ... arXiv preprint arXiv:2209.03839, 2022 | | 2022 |
| Enhancement of Attack Detection Technology using AI with Synthetic-Log Generation T Yamamoto, T Nakai, R Otsuka, Y Wang, KJ Kim, T Koike-Akino, ... 2022 Symposium on Cryptography and Information Security, 2022 | | 2022 |
| Build a Computationally Efficient Strong Defense Against Adversarial Example Attacks C Liu, L DiValentin, A Ding, MB Salem | | |
