Nathaniel D. Bastian

According to our database, Nathaniel D. Bastian authored at least 61 papers between 2013 and 2024.

Collaborative distances:

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

2024

Constrained optimization based adversarial example generation for transfer attacks in network intrusion detection systems.

Marc Chalé, Bruce Cox, Jeffery Weir, Nathaniel D. Bastian

Optim. Lett., December, 2024

A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System.

Zong-Zhi Lin, Thomas D. Pike, Mark M. Bailey, Nathaniel D. Bastian

IEEE Trans. Syst. Man Cybern. Syst., November, 2024

Multi-Memristor Based Distributed Decision Tree Circuit for Cybersecurity Applications.

Lei Zhang, Joseph Riem, Jingdi Chen, Henry Mackay, Tian Lan, Nathaniel D. Bastian, Gina C. Adam

IEEE Trans. Circuits Syst. I Regul. Pap., August, 2024

Human Intuition and Algorithmic Efficiency Must Be Balanced to Enhance Data Mesh Resilience.

Andrew Strelzoff, Benjamin D. Trump, Christopher L. Cummings, Madison Smith, Stephanie Elisabeth Galaitsi, Kelsey Stoddard, Jeffrey M. Keisler, Moshe Y. Vardi, Nathaniel D. Bastian, Alexander Kott, Igor Linkov

Commun. ACM, May, 2024

ACI IoT Network Traffic Dataset 2023.

Nathaniel D. Bastian, David A. Bierbrauer, Morgan McKenzie, Emily Nack

Dataset, April, 2024

XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language Model.

Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian

CoRR, 2024

A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI.

Alice Bizzarri, Chung-En Yu, Brian Jalaian, Fabrizio Riguzzi, Nathaniel D. Bastian

CoRR, 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

A sequential deep learning framework for a robust and resilient network intrusion detection system.

Soumyadeep Hore, Jalal Ghadermazi, Ankit Shah, Nathaniel D. Bastian

Comput. Secur., 2024

AIS-NIDS: An intelligent and self-sustaining network intrusion detection system.

Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian

Comput. Secur., 2024

Seeing the Whole Elephant - A Comprehensive Framework for Data Education.

Iain J. Cruickshank, Nathaniel D. Bastian, Jean R. S. Blair, Christa M. Chewar, Edward Sobiesk

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Predicting F1-Scores of Classifiers in Network Intrusion Detection Systems.

Priscila Silva, Gaspard Baye, Alexandre Broggi, Nathaniel D. Bastian, Gökhan Kul, Lance Fiondella

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

A Neuro-Symbolic Artificial Intelligence Network Intrusion Detection System.

Alice Bizzarri, Brian Jalaian, Fabrizio Riguzzi, Nathaniel D. Bastian

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

2023

SeNet-I: An approach for detecting network intrusions through serialized network traffic images.

Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian

Eng. Appl. Artif. Intell., November, 2023

Deep VULMAN: A deep reinforcement learning-enabled cyber vulnerability management framework.

Soumyadeep Hore, Ankit Shah, Nathaniel D. Bastian

Expert Syst. Appl., July, 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

Real-time Network Intrusion Detection via Decision Transformers.

Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina C. Adam, Nathaniel D. Bastian, Tian Lan

CoRR, 2023

Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving.

Sumit Kumar Jha, Susmit Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Rickard Ewetz, Sandeep Neema

CoRR, 2023

Analysis of Media Writing Style Bias through Text-Embedding Networks.

Iain J. Cruickshank, Jessica Zhu, Nathaniel D. Bastian

CoRR, 2023

Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation.

Soumyadeep Hore, Jalal Ghadermazi, Diwas Paudel, Ankit Shah, Tapas K. Das, Nathaniel D. Bastian

CoRR, 2023

Measuring Classification Decision Certainty and Doubt.

Alexander M. Berenbeim, Iain J. Cruickshank, Susmit Jha, Robert H. Thomson, Nathaniel D. Bastian

CoRR, 2023

Uncertainty-Quantified, Robust Deep Learning for Network Intrusion Detection.

Joshua A. Wong, Alexander M. Berenbeim, David A. Bierbrauer, Nathaniel D. Bastian

Proceedings of the Winter Simulation Conference, 2023

Performance Analysis of Deep-Learning Based Open Set Recognition Algorithms for Network Intrusion Detection Systems.

Gaspard Baye, Priscila Silva, Alexandre Broggi, Lance Fiondella, Nathaniel D. Bastian, Gökhan Kul

Proceedings of the NOMS 2023, 2023

Challenges and Opportunities in Neuro-Symbolic Composition of Foundation Models.

Susmit Jha, Anirban Roy, Adam D. Cobb, Alexander M. Berenbeim, Nathaniel D. Bastian

Proceedings of the IEEE Military Communications Conference, 2023

Counterexample Guided Inductive Synthesis Using Large Language Models and Satisfiability Solving.

Sumit Kumar Jha, Susmit Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Rickard Ewetz, Sandeep Neema

Proceedings of the IEEE Military Communications Conference, 2023

Neurosymbolic AI in Cybersecurity: Bridging Pattern Recognition and Symbolic Reasoning.

Brian Jalaian, Nathaniel D. Bastian

Proceedings of the IEEE Military Communications Conference, 2023

Detecting Unknown Attacks in IoT Environments: An Open Set Classifier for Enhanced Network Intrusion Detection.

Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian

Proceedings of the IEEE Military Communications Conference, 2023

Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting.

Susmit Jha, Sumit Kumar Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Sandeep Neema

Proceedings of the IEEE International Conference on Assured Autonomy, 2023

Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification.

Taylor Bradley, Elie Alhajjar, Nathaniel D. Bastian

Proceedings of the IEEE International Conference on Assured Autonomy, 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

Towards Robust Learning using Diametrical Risk Minimization for Network Intrusion Detection.

Kelson J. McCollum, Nathaniel D. Bastian, Johannes O. Royset

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

Empirical Evaluation of Autoencoder Models for Anomaly Detection in Packet-based NIDS.

Soumyadeep Hore, Quoc H. Nguyen, Yulun Xu, Ankit Shah, Nathaniel D. Bastian, Trung Le

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

RIDE: Real-time Intrusion Detection via Explainable Machine Learning Implemented in a Memristor Hardware Architecture.

Jingdi Chen, Lei Zhang, Joseph Riem, Gina C. Adam, Nathaniel D. Bastian, Tian Lan

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

2022

A ranked solution for social media fact checking using epidemic spread modeling.

John H. Smith, Nathaniel D. Bastian

Inf. Sci., 2022

Generating realistic cyber data for training and evaluating machine learning classifiers for network intrusion detection systems.

Marc Chalé, Nathaniel D. Bastian

Expert Syst. Appl., 2022

Off-Policy Evaluation for Action-Dependent Non-stationary Environments.

Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno C. da Silva, Emma Brunskill, Philip S. Thomas

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Context-aware Collaborative Neuro-Symbolic Inference in IoBTs.

Tarek F. Abdelzaher, Nathaniel D. Bastian, Susmit Jha, Lance M. Kaplan, Mani B. Srivastava, Venugopal V. Veeravalli

Proceedings of the IEEE Military Communications Conference, 2022

Payload-Byte: A Tool for Extracting and Labeling Packet Capture Files of Modern Network Intrusion Detection Datasets.

Yasir Ali Farrukh, Irfan Khan, Syed Wali, David A. Bierbrauer, John A. Pavlik, Nathaniel D. Bastian

Proceedings of the IEEE/ACM International Conference on Big Data Computing, 2022

2021

Adversarial machine learning in Network Intrusion Detection Systems.

Elie Alhajjar, Paul Maxwell, Nathaniel D. Bastian

Expert Syst. Appl., 2021

Anomaly Detection in Cybersecurity: Unsupervised, Graph-Based and Supervised Learning Methods in Adversarial Environments.

David A. Bierbrauer, Alexander Chang, Will Kritzer, Nathaniel D. Bastian

CoRR, 2021

Robust Decision-Making in the Internet of Battlefield Things Using Bayesian Neural Networks.

Adam D. Cobb, Brian Jalaian, Nathaniel D. Bastian, Stephen Russell

Proceedings of the Winter Simulation Conference, 2021

CHALLENGES AND OPPORTUNITIES FOR GENERATIVE METHODS IN THE CYBER DOMAIN.

Marc Chalé, Nathaniel D. Bastian

Proceedings of the Winter Simulation Conference, 2021

A Sensitivity Analysis of Poisoning and Evasion Attacks in Network Intrusion Detection System Machine Learning Models.

Kevin Talty, John Stockdale, Nathaniel D. Bastian

Proceedings of the 2021 IEEE Military Communications Conference, 2021

An Adversarial Training Based Machine Learning Approach to Malware Classification under Adversarial Conditions.

Sean M. Devine, Nathaniel D. Bastian

Proceedings of the 54th Hawaii International Conference on System Sciences, 2021

Evaluating Model Robustness to Adversarial Samples in Network Intrusion Detection.

Madeleine Schneider, David Aspinall, Nathaniel D. Bastian

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

The spatially conscious machine learning model.

Timothy J. Kiely, Nathaniel D. Bastian

Stat. Anal. Data Min., 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

Stacked Generalizations in Imbalanced Fraud Data Sets using Resampling Methods.

Kathleen Kerwin, Nathaniel D. Bastian

CoRR, 2020

Algorithm selection framework for cyber attack detection.

Marc Chalé, Nathaniel D. Bastian, Jeffery Weir

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

2019

Intelligent Systems Design for Malware Classification Under Adversarial Conditions.

Sean M. Devine, Nathaniel D. Bastian

CoRR, 2019

Solving The Army's Cyber Workforce Planning Problem Using Stochastic Optimization and Discrete-Event Simulation Modeling.

Nathaniel D. Bastian, Christopher B. Fisher, Andrew O. Hall, Brian J. Lunday

Proceedings of the 2019 Winter Simulation Conference, 2019

Intelligent Feature Engineering for Cybersecurity.

Paul Maxwell, Elie Alhajjar, Nathaniel D. Bastian

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2017

Optimizing Student Team and Job Assignments for the Holy Family Academy.

Sharan Srinivas, Mohammadmahdi Alizadeh, Nathaniel D. Bastian

Interfaces, 2017

A hybrid recommender system using artificial neural networks.

Tulasi K. Paradarami, Nathaniel D. Bastian, Jennifer L. Wightman

Expert Syst. Appl., 2017

Machine Learning and Statistical Techniques to Predict Sepsis: Unifying Previous Work.

Joseph Klobusický, Alexander Murph, Alexander C. Robinson, Nathaniel D. Bastian, Paul M. Griffin, Shravan Kethireddy, Nathan Ryan

Proceedings of the Summit on Clinical Research Informatics, 2017

2016

Multi-criteria logistics modeling for military humanitarian assistance and disaster relief aerial delivery operations.

Nathaniel D. Bastian, Paul M. Griffin, Eric Spero, Lawrence V. Fulton

Optim. Lett., 2016

Data analytics in health promotion: Health market segmentation and classification of total joint replacement surgery patients.

Eric R. Swenson, Nathaniel D. Bastian, Harriet Black Nembhard

Expert Syst. Appl., 2016

2015

A maximum expected covering problem for locating and dispatching two classes of military medical evacuation air assets.

Benjamin C. Grannan, Nathaniel D. Bastian, Laura A. McLay

Optim. Lett., 2015

The AMEDD Uses Goal Programming to Optimize Workforce Planning Decisions.

Nathaniel D. Bastian, Pat McMurry, Lawrence V. Fulton, Paul M. Griffin, Shisheng Cui, Thor Hanson, Sharan Srinivas

Interfaces, 2015

2013

Rainwater harvesting system using a non-parametric stochastic rainfall generator.

Lawrence V. Fulton, Nathaniel D. Bastian, Francis A. Méndez Mediavilla, Rasim Muzaffer Musal

Simul., 2013