Michael J. De Lucia

According to our database1, Michael J. De Lucia authored at least 24 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Robust and Explainable Divide-and-Conquer Learning for Intrusion Detection.
CoRR, May, 2026

SPRINT: Semi-supervised Prototypical Representation for Few-Shot Class-Incremental Tabular Learning.
CoRR, March, 2026

CLUE: Bringing Machine Unlearning to Mobile Devices.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2026

What Do They Fix? LLM-Aided Categorization of Security Patches for Critical Memory Bugs.
Proceedings of the 33rd Annual Network and Distributed System Security Symposium, 2026

2025
NOMAD - Navigating Optimal Model Application to Datastreams.
CoRR, November, 2025

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification.
CoRR, May, 2025

MalVis: Large-Scale Bytecode Visualization Framework for Explainable Android Malware Detection.
J. Cybersecur. Priv., 2025

NI-Diff: Zero-Day and Adversarial Network Intrusion Detection with Diffusion Models.
Proceedings of the IEEE Military Communications Conference, 2025

SSPNet: Semi-Supervised Prototypical Networks for Few-Shot Network Intrusion Detection.
Proceedings of the IEEE Military Communications Conference, 2025

Model-agnostic clean-label backdoor mitigation in cybersecurity environments.
Proceedings of the IEEE Military Communications Conference, 2025

Resilient Wireless Communications with Selective Deep Neural Network Classification.
Proceedings of the IEEE Military Communications Conference, 2025

ClusterFed: Self-supervised Federated Network Intrusion Detection using Clustering.
Proceedings of the IEEE Military Communications Conference, 2025

On the Adversarial Vulnerability of Label-Free Test-Time Adaptation.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
TrojFM: Resource-efficient Backdoor Attacks against Very Large Foundation Models.
CoRR, 2024

A topological data analysis approach for detecting data poisoning attacks against machine learning based network intrusion detection systems.
Comput. Secur., 2024

Improving Android Malware Detection with Entropy Bytecode-to-Image Encoding Framework.
Proceedings of the 33rd International Conference on Computer Communications and Networks, 2024

2023
Transfer learning for raw network traffic detection.
Expert Syst. Appl., 2023

Preprocessing Network Traffic using Topological Data Analysis for Data Poisoning Detection.
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.
Proceedings of the 2021 IEEE Military Communications Conference, 2021

Themis: Ambiguity-Aware Network Intrusion Detection based on Symbolic Model Comparison.
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.
CoRR, 2020

A network security classifier defense: against adversarial machine learning attacks.
Proceedings of the 2nd ACM Workshop on Wireless Security and Machine Learning, 2020

2019
Features and Operation of an Autonomous Agent for Cyber Defense.
CoRR, 2019

Detection of Encrypted Malicious Network Traffic using Machine Learning.
Proceedings of the 2019 IEEE Military Communications Conference, 2019


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