| Keeping the bad guys out: Protecting and vaccinating deep learning with jpeg compression N Das, M Shanbhogue, ST Chen, F Hohman, L Chen, ME Kounavis, ... arXiv preprint arXiv:1705.02900, 2017 | 378 | 2017 |
| Shield: Fast, practical defense and vaccination for deep learning using jpeg compression N Das, M Shanbhogue, ST Chen, F Hohman, S Li, L Chen, ME Kounavis, ... Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 251 | 2018 |
| Mapping archaeological landscapes from space DC Comer, MJ Harrower Springer 5, 159-171, 2013 | 131 | 2013 |
| Deep transfer learning for static malware classification L Chen arXiv preprint arXiv:1812.07606, 2018 | 70 | 2018 |
| Henet: A deep learning approach on intel® processor trace for effective exploit detection L Chen, S Sultana, R Sahita 2018 IEEE Security and Privacy Workshops (SPW), 109-115, 2018 | 63* | 2018 |
| Deep learning on execution trace data for exploit detection L Chen, S Sultana US Patent 10,915,631, 2021 | 56 | 2021 |
| Spectral clustering for divide-and-conquer graph matching V Lyzinski, DL Sussman, DE Fishkind, H Pao, L Chen, JT Vogelstein, ... Parallel Computing 47, 70-87, 2015 | 55 | 2015 |
| Simulation of the hydrological and environmental effects of a sponge city based on MIKE FLOOD J Li, B Zhang, C Mu, L Chen Environmental earth sciences 77, 1-16, 2018 | 51 | 2018 |
| ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio N Das, M Shanbhogue, ST Chen, L Chen, ME Kounavis, DH Chau Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 49 | 2019 |
| Vertex Nomination Schemes for Membership Prediction DE Fishkind, V Lyzinski, H Pao, L Chen, CE Priebe Annuals of Applied Statistics, accepted for publication. arXiv preprint …, 2015 | 39 | 2015 |
| A joint graph inference case study: the c. elegans chemical and electrical connectomes L Chen, JT Vogelstein, V Lyzinski, CE Priebe Worm. http://www.tandfonline.com/doi/full/10.1080/21624054.2016.1142041 …, 2015 | 36 | 2015 |
| Towards resilient machine learning for ransomware detection L Chen, CY Yang, A Paul, R Sahita arXiv preprint arXiv:1812.09400, 2018 | 31 | 2018 |
| POSTER: Semi-supervised classification for dynamic android malware detection L Chen, M Zhang, CY Yang, R Sahita Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications …, 2017 | 28 | 2017 |
| Stamina: scalable deep learning approach for malware classification L Chen, R Sahita, J Parikh, M Marino Intel Labs Whitepaper, 2020 | 25 | 2020 |
| Semi-supervised classification for dynamic Android malware detection L Chen, M Zhang, CY Yang, R Sahita https://arxiv.org/abs/1704.05948, 2017 | 23 | 2017 |
| On the robustness of monte carlo dropout trained with noisy labels P Goel, L Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 22 | 2021 |
| Trust model for malware classification L Chen US Patent App. 16/367,611, 2019 | 21 | 2019 |
| System, apparatus and method for detecting a data-oriented programming attack L Chen, RL Sahita US Patent 10,503,902, 2019 | 20 | 2019 |
| Robust Vertex Classification L Chen, C Shen, J Vogelstein, C Priebe IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted for …, 2015 | 20 | 2015 |
| Barnum: Detecting Document Malware via Control Flow Anomalies in Hardware Traces C Yagemann, S Sultana, L Chen, W Lee Information Security: 22nd International Conference, ISC 2019, New York City …, 2019 | 19 | 2019 |
