| Deep learning for unsupervised insider threat detection in structured cybersecurity data streams A Tuor, S Kaplan, B Hutchinson, N Nichols, S Robinson Workshops at the Thirty-First AAAI Conference on Artificial Intelligence, 2017 | 417 | 2017 |
| Recurrent neural network attention mechanisms for interpretable system log anomaly detection A Brown, A Tuor, B Hutchinson, N Nichols Proceedings of the first workshop on machine learning for computing systems, 1-8, 2018 | 226 | 2018 |
| Recurrent neural network language models for open vocabulary event-level cyber anomaly detection AR Tuor, R Baerwolf, N Knowles, B Hutchinson, N Nichols, R Jasper Workshops at the thirty-second AAAI conference on artificial intelligence, 2018 | 59 | 2018 |
| Systematic evaluation of backdoor data poisoning attacks on image classifiers L Truong, C Jones, B Hutchinson, A August, B Praggastis, R Jasper, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 46 | 2020 |
| Faster fuzzing: Reinitialization with deep neural models N Nichols, M Raugas, R Jasper, N Hilliard arXiv preprint arXiv:1711.02807, 2017 | 40 | 2017 |
| Bridging automated to autonomous cyber defense: Foundational analysis of tabular q-learning A Applebaum, C Dennler, P Dwyer, M Moskowitz, H Nguyen, N Nichols, ... Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security …, 2022 | 17 | 2022 |
| Projecting trouble: Light based adversarial attacks on deep learning classifiers N Nichols, R Jasper arXiv preprint arXiv:1810.10337, 2018 | 10 | 2018 |
| Deep learning for unsupervised insider threat detection in structured cybersecurity data streams. arXiv 2017 A Tuor, S Kaplan, B Hutchinson, N Nichols, S Robinson arXiv preprint arXiv:1710.00811, 0 | 9 | |
| Predicting user roles from computer logs using recurrent neural networks A Tuor, S Kaplan, B Hutchinson, N Nichols, S Robinson Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 7 | 2017 |
| Deep learning for unsupervised insider threat detection in structured cybersecurity data streams. arXiv A Tuor, S Kaplan, B Hutchinson, N Nichols, S Robinson arXiv preprint arXiv:1710.00811, 2017 | 6 | 2017 |
| Deep learning for unsupervised insider threat detection in structured cybersecurity data streams (2017) A Tuor, S Kaplan, B Hutchinson, N Nichols, S Robinson arXiv preprint arXiv:1710.00811, 2014 | 6 | 2014 |
| Marine mammal species detection and classification NM Nichols | 5 | 2016 |
| Beyond cage: Investigating generalization of learned autonomous network defense policies M Wolk, A Applebaum, C Dennler, P Dwyer, M Moskowitz, H Nguyen, ... arXiv preprint arXiv:2211.15557, 2022 | 4 | 2022 |
| Weakly supervised click models for odontocete species classification N Nichols, M Ostendorf OCEANS 2014-TAIPEI, 1-4, 2014 | 2 | 2014 |
| Identification of program signatures from cloud computing system telemetry data N Nichols, M Greaves, W Smith, R LaMothe, G Longoni, J Teuton 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-5, 2016 | 1 | 2016 |
| Call and component evaluation for improved performance of recognition of killer whale individuals N Nichols, L Atlas, A Bowles, MA Roch OCEANS 2010 MTS/IEEE SEATTLE, 1-4, 2010 | 1 | 2010 |
| Recognition of killer whale individuals from multiple stereotyped call types. N Nichols, L Atlas, A Bowles, M Roch The Journal of the Acoustical Society of America 127 (3_Supplement), 1970-1970, 2010 | 1 | 2010 |
| Recognition of Killer Whale Individuals from Passive Acoustics: An Application of Human Speaker Recognition NM Nichols University of Washington, 2010 | 1 | 2010 |
| The Future of Cyber Systems: Human-AI Reinforcement Learning with Adversarial Robustness N Nichols The Second Workshop on New Frontiers in Adversarial Machine Learning, 2023 | | 2023 |
| Machine Learning Algorithms for Active Monitoring of High Performance Computing as a Service (HPCaaS) Cloud Environments G Longoni, R LaMothe, J Teuton, M Greaves, N Nichols, W Smith arXiv preprint arXiv:2009.12498, 2020 | | 2020 |
