Michael J. De Lucia

According to our database, Michael J. De Lucia authored at least 15 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

NOMAD - Navigating Optimal Model Application to Datastreams.

Ashwin Gerard Colaco, Sharad Mehrotra, Michael J. De Lucia, Kevin W. Hamlen, Murat Kantarcioglu, Latifur Khan, Ananthram Swami, Bhavani Thuraisingham

CoRR, November, 2025

What Do They Fix? LLM-Aided Categorization of Security Patches for Critical Memory Bugs.

Xingyu Li, Juefei Pu, Yifan Wu, Xiaochen Zou, Shitong Zhu, Qiushi Wu, Zheng Zhang, Joshua Hsu, Yue Dong, Zhiyun Qian, Kangjie Lu, Trent Jaeger, Michael J. De Lucia, Srikanth V. Krishnamurthy

CoRR, September, 2025

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification.

Saleh J. Makkawy, Michael J. De Lucia, Kenneth E. Barner

CoRR, May, 2025

On the Adversarial Vulnerability of Label-Free Test-Time Adaptation.

Shahriar Rifat, Jonathan D. Ashdown, Michael J. De Lucia, Ananthram Swami, Francesco Restuccia

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

TrojFM: Resource-efficient Backdoor Attacks against Very Large Foundation Models.

Yuzhou Nie, Yanting Wang, Jinyuan Jia, Michael J. De Lucia, Nathaniel D. Bastian, Wenbo Guo, Dawn Song

CoRR, 2024

A topological data analysis approach for detecting data poisoning attacks against machine learning based network intrusion detection systems.

Galamo Monkam, Michael J. De Lucia, Nathaniel D. Bastian

Comput. Secur., 2024

Improving Android Malware Detection with Entropy Bytecode-to-Image Encoding Framework.

Saleh J. Makkawy, Abdalrahman Alblwi, Michael J. De Lucia, Kenneth E. Barner

Proceedings of the 33rd International Conference on Computer Communications and Networks, 2024

2023

Transfer learning for raw network traffic detection.

David A. Bierbrauer, Michael J. De Lucia, Krishna Reddy, Paul Maxwell, Nathaniel D. Bastian

Expert Syst. Appl., 2023

Preprocessing Network Traffic using Topological Data Analysis for Data Poisoning Detection.

Galamo Monkam, Michael J. De Lucia, Nathaniel D. Bastian

Proceedings of the IEEE Conference on Dependable and Secure Computing, 2023

2021

Poisoning Attacks and Data Sanitization Mitigations for Machine Learning Models in Network Intrusion Detection Systems.

Sridhar Venkatesan, Harshvardhan Sikka, Rauf Izmailov, Ritu Chadha, Alina Oprea, Michael J. De Lucia

Proceedings of the 2021 IEEE Military Communications Conference, 2021

Themis: Ambiguity-Aware Network Intrusion Detection based on Symbolic Model Comparison.

Zhongjie Wang, Shitong Zhu, Keyu Man, Pengxiong Zhu, Yu Hao, Zhiyun Qian, Srikanth V. Krishnamurthy, Tom La Porta, Michael J. De Lucia

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020

Advancing the Research and Development of Assured Artificial Intelligence and Machine Learning Capabilities.

Tyler J. Shipp, Daniel J. Clouse, Michael J. De Lucia, Metin B. Ahiskali, Kai Steverson, Jonathan M. Mullin, Nathaniel D. Bastian

CoRR, 2020

A network security classifier defense: against adversarial machine learning attacks.

Michael J. De Lucia, Chase Cotton

Proceedings of the 2nd ACM Workshop on Wireless Security and Machine Learning, 2020

2019

Features and Operation of an Autonomous Agent for Cyber Defense.

Michael J. De Lucia, Allison Newcomb, Alexander Kott

CoRR, 2019

Detection of Encrypted Malicious Network Traffic using Machine Learning.

Michael J. De Lucia, Chase Cotton

Proceedings of the 2019 IEEE Military Communications Conference, 2019