| Detection of Encrypted Malicious Network Traffic using Machine Learning MJ De Lucia, C Cotton MILCOM 2019-2019 IEEE Military Communications Conference (MILCOM), 1-6, 2019 | 33 | 2019 |
| Machine learning raw network traffic detection MJ De Lucia, PE Maxwell, ND Bastian, A Swami, B Jalaian, N Leslie Artificial Intelligence and Machine Learning for Multi-Domain Operations …, 2021 | 23 | 2021 |
| A survey on security isolation of virtualization, containers, and unikernels MJ De Lucia US Army Research Laboratory Aberdeen Proving Ground United States, 2017 | 20 | 2017 |
| Transfer learning for raw network traffic detection DA Bierbrauer, MJ De Lucia, K Reddy, P Maxwell, ND Bastian Expert Systems with Applications 211, 118641, 2023 | 18 | 2023 |
| Poisoning Attacks and Data Sanitization Mitigations for Machine Learning Models in Network Intrusion Detection Systems S Venkatesan, H Sikka, R Izmailov, R Chadha, A Oprea, MJ De Lucia MILCOM 2021-2021 IEEE Military Communications Conference (MILCOM), 874-879, 2021 | 17 | 2021 |
| Adversarial Machine Learning for Cyber Security MJ De Lucia, C Cotton Journal of Information Systems Applied Research 12 (1), 26, 2019 | 17 | 2019 |
| Features and Operation of an Autonomous Agent for Cyber Defense MJ De Lucia, A Newcomb, A Kott arXiv preprint arXiv:1905.05253, 2019 | 12 | 2019 |
| Identifying and detecting applications within TLS traffic MJ De Lucia, C Cotton Cyber Sensing 2018 10630, 106300U, 2018 | 11 | 2018 |
| A network security classifier defense: against adversarial machine learning attacks MJ De Lucia, C Cotton Proceedings of the 2nd ACM Workshop on Wireless Security and Machine …, 2020 | 9 | 2020 |
| Importance of features in adversarial machine learning for cyber security M De Lucia, C Cotton Proceedings of the Conference on Information Systems Applied Research ISSN …, 2018 | 6 | 2018 |
| Advancing the Research and Development of Assured Artificial Intelligence and Machine Learning Capabilities TJ Shipp, DJ Clouse, MJ De Lucia, MB Ahiskali, K Steverson, JM Mullin, ... arXiv preprint arXiv:2009.13250, 2020 | 5 | 2020 |
| Themis: Ambiguity-aware network intrusion detection based on symbolic model comparison Z Wang, S Zhu, K Man, P Zhu, Y Hao, Z Qian, SV Krishnamurthy, ... Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 4 | 2021 |
| Data Fidelity in the Post-Truth Era Part 1: Network Data M De Lucia, S Hutchinson, C Sample, CC Sample ICCWS 2018 13th International Conference on Cyber Warfare and Security, 149, 2018 | 3 | 2018 |
| Cloud migration experiment configuration and results M De Lucia, J Wray, SS Collmann US Army Research Laboratory Aberdeen Proving Ground United States, 2017 | 2 | 2017 |
| Poisoning attacks on machine learning models in cyber systems and mitigation strategies R Izmailov, S Venkatesan, A Reddy, R Chadha, M De Lucia, A Oprea Disruptive Technologies in Information Sciences VI 12117, 1211702, 2022 | 1 | 2022 |
| Approaches to Prediction of Cyber Events: Report of the 2017 Specialist Meeting by the North Atlantic Treaty Organization (NATO) Research Group IST-145-RTG D McCallam, T Braun, M Delucia, G Shearer, N Leslie, P Ritchey, ... ARMY RESEARCH LAB ABERDEEN PROVING GROUND United States, 2019 | 1 | 2019 |
| A Topological Data Analysis Approach for Detecting Data Poisoning Attacks Against Machine Learning Based Network Intrusion Detection Systems G Monkam, M De Lucia, N Bastian Available at SSRN 4640844, 2023 | | 2023 |
| Preprocessing Network Traffic using Topological Data Analysis for Data Poisoning Detection GF Monkam, MJ De Lucia, ND Bastian 2023 IEEE Conference on Dependable and Secure Computing (DSC), 1-8, 2023 | | 2023 |
| Machine Learning Enhanced Network Security MJ De Lucia PQDT-UK & Ireland, 2020 | | 2020 |
| Network-Resilience Modeling and Intrusion Detection N Leslie, M De Lucia Resilience and Hybrid Threats, 94-101, 2019 | | 2019 |
Chase CottonProfessor, Electrical and Computer Engineering, University of Delaware; CISSPudel.edu üzerinde doğrulanmış e-posta adresine sahip
