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Nathaniel D. Bastian
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Journal Articles
- 2024
- [j18]Soumyadeep Hore, Jalal Ghadermazi, Ankit Shah, Nathaniel D. Bastian:
A sequential deep learning framework for a robust and resilient network intrusion detection system. Comput. Secur. 144: 103928 (2024) - [j17]Galamo Monkam, Michael J. De Lucia, Nathaniel D. Bastian:
A topological data analysis approach for detecting data poisoning attacks against machine learning based network intrusion detection systems. Comput. Secur. 144: 103929 (2024) - [j16]Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian:
AIS-NIDS: An intelligent and self-sustaining network intrusion detection system. Comput. Secur. 144: 103982 (2024) - [j15]Lei Zhang, Joseph Riem, Jingdi Chen, Henry Mackay, Tian Lan, Nathaniel D. Bastian, Gina C. Adam:
Multi-Memristor Based Distributed Decision Tree Circuit for Cybersecurity Applications. IEEE Trans. Circuits Syst. I Regul. Pap. 71(8): 3526-3537 (2024) - 2023
- [j14]Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian:
SeNet-I: An approach for detecting network intrusions through serialized network traffic images. Eng. Appl. Artif. Intell. 126(Part D): 107169 (2023) - [j13]David A. Bierbrauer, Michael J. De Lucia, Krishna Reddy, Paul Maxwell, Nathaniel D. Bastian:
Transfer learning for raw network traffic detection. Expert Syst. Appl. 211: 118641 (2023) - [j12]Soumyadeep Hore, Ankit Shah, Nathaniel D. Bastian:
Deep VULMAN: A deep reinforcement learning-enabled cyber vulnerability management framework. Expert Syst. Appl. 221: 119734 (2023) - 2022
- [j11]Marc Chalé, Nathaniel D. Bastian:
Generating realistic cyber data for training and evaluating machine learning classifiers for network intrusion detection systems. Expert Syst. Appl. 207: 117936 (2022) - [j10]John H. Smith, Nathaniel D. Bastian:
A ranked solution for social media fact checking using epidemic spread modeling. Inf. Sci. 589: 550-563 (2022) - 2021
- [j9]Elie Alhajjar, Paul Maxwell, Nathaniel D. Bastian:
Adversarial machine learning in Network Intrusion Detection Systems. Expert Syst. Appl. 186: 115782 (2021) - 2020
- [j8]Timothy J. Kiely, Nathaniel D. Bastian:
The spatially conscious machine learning model. Stat. Anal. Data Min. 13(1): 31-49 (2020) - 2017
- [j7]Tulasi K. Paradarami, Nathaniel D. Bastian, Jennifer L. Wightman:
A hybrid recommender system using artificial neural networks. Expert Syst. Appl. 83: 300-313 (2017) - [j6]Sharan Srinivas, Mohammadmahdi Alizadeh, Nathaniel D. Bastian:
Optimizing Student Team and Job Assignments for the Holy Family Academy. Interfaces 47(2): 163-174 (2017) - 2016
- [j5]Eric R. Swenson, Nathaniel D. Bastian, Harriet Black Nembhard:
Data analytics in health promotion: Health market segmentation and classification of total joint replacement surgery patients. Expert Syst. Appl. 60: 118-129 (2016) - [j4]Nathaniel D. Bastian, Paul M. Griffin, Eric Spero, Lawrence V. Fulton:
Multi-criteria logistics modeling for military humanitarian assistance and disaster relief aerial delivery operations. Optim. Lett. 10(5): 921-953 (2016) - 2015
- [j3]Nathaniel D. Bastian, Pat McMurry, Lawrence V. Fulton, Paul M. Griffin, Shisheng Cui, Thor Hanson, Sharan Srinivas:
The AMEDD Uses Goal Programming to Optimize Workforce Planning Decisions. Interfaces 45(4): 305-324 (2015) - [j2]Benjamin C. Grannan, Nathaniel D. Bastian, Laura A. McLay:
A maximum expected covering problem for locating and dispatching two classes of military medical evacuation air assets. Optim. Lett. 9(8): 1511-1531 (2015) - 2013
- [j1]Lawrence V. Fulton, Nathaniel D. Bastian, Francis A. Méndez Mediavilla, Rasim Muzaffer Musal:
Rainwater harvesting system using a non-parametric stochastic rainfall generator. Simul. 89(6): 693-702 (2013)
Conference and Workshop Papers
- 2024
- [c27]Alice Bizzarri, Brian Jalaian, Fabrizio Riguzzi, Nathaniel D. Bastian:
A Neuro-Symbolic Artificial Intelligence Network Intrusion Detection System. ICCCN 2024: 1-9 - [c26]Priscila Silva, Gaspard Baye, Alexandre Broggi, Nathaniel D. Bastian, Gökhan Kul, Lance Fiondella:
Predicting F1-Scores of Classifiers in Network Intrusion Detection Systems. ICCCN 2024: 1-6 - [c25]Iain J. Cruickshank, Nathaniel D. Bastian, Jean R. S. Blair, Christa M. Chewar, Edward Sobiesk:
Seeing the Whole Elephant - A Comprehensive Framework for Data Education. SIGCSE (1) 2024: 248-254 - 2023
- [c24]Jingdi Chen, Lei Zhang, Joseph Riem, Gina C. Adam, Nathaniel D. Bastian, Tian Lan:
RIDE: Real-time Intrusion Detection via Explainable Machine Learning Implemented in a Memristor Hardware Architecture. DSC 2023: 1-8 - [c23]Soumyadeep Hore, Quoc H. Nguyen, Yulun Xu, Ankit Shah, Nathaniel D. Bastian, Trung Le:
Empirical Evaluation of Autoencoder Models for Anomaly Detection in Packet-based NIDS. DSC 2023: 1-8 - [c22]Kelson J. McCollum, Nathaniel D. Bastian, Johannes O. Royset:
Towards Robust Learning using Diametrical Risk Minimization for Network Intrusion Detection. DSC 2023: 1-8 - [c21]Galamo Monkam, Michael J. De Lucia, Nathaniel D. Bastian:
Preprocessing Network Traffic using Topological Data Analysis for Data Poisoning Detection. DSC 2023: 1-8 - [c20]Taylor Bradley, Elie Alhajjar, Nathaniel D. Bastian:
Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification. ICAA 2023: 11-18 - [c19]Susmit Jha, Sumit Kumar Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Sandeep Neema:
Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting. ICAA 2023: 149-152 - [c18]Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian:
Detecting Unknown Attacks in IoT Environments: An Open Set Classifier for Enhanced Network Intrusion Detection. MILCOM 2023: 121-126 - [c17]Susmit Jha, Anirban Roy, Adam D. Cobb, Alexander M. Berenbeim, Nathaniel D. Bastian:
Challenges and Opportunities in Neuro-Symbolic Composition of Foundation Models. MILCOM 2023: 156-161 - [c16]Brian Jalaian, Nathaniel D. Bastian:
Neurosymbolic AI in Cybersecurity: Bridging Pattern Recognition and Symbolic Reasoning. MILCOM 2023: 268-273 - [c15]Sumit Kumar Jha, Susmit Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Rickard Ewetz, Sandeep Neema:
Counterexample Guided Inductive Synthesis Using Large Language Models and Satisfiability Solving. MILCOM 2023: 944-949 - [c14]Gaspard Baye, Priscila Silva, Alexandre Broggi, Lance Fiondella, Nathaniel D. Bastian, Gökhan Kul:
Performance Analysis of Deep-Learning Based Open Set Recognition Algorithms for Network Intrusion Detection Systems. NOMS 2023: 1-6 - [c13]Joshua A. Wong, Alexander M. Berenbeim, David A. Bierbrauer, Nathaniel D. Bastian:
Uncertainty-Quantified, Robust Deep Learning for Network Intrusion Detection. WSC 2023: 2470-2481 - 2022
- [c12]Yasir Ali Farrukh, Irfan Khan, Syed Wali, David A. Bierbrauer, John A. Pavlik, Nathaniel D. Bastian:
Payload-Byte: A Tool for Extracting and Labeling Packet Capture Files of Modern Network Intrusion Detection Datasets. BDCAT 2022: 58-67 - [c11]Tarek F. Abdelzaher, Nathaniel D. Bastian, Susmit Jha, Lance M. Kaplan, Mani B. Srivastava, Venugopal V. Veeravalli:
Context-aware Collaborative Neuro-Symbolic Inference in IoBTs. MILCOM 2022: 1053-1058 - [c10]Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno C. da Silva, Emma Brunskill, Philip S. Thomas:
Off-Policy Evaluation for Action-Dependent Non-stationary Environments. NeurIPS 2022 - 2021
- [c9]Madeleine Schneider, David Aspinall, Nathaniel D. Bastian:
Evaluating Model Robustness to Adversarial Samples in Network Intrusion Detection. IEEE BigData 2021: 3343-3352 - [c8]Sean M. Devine, Nathaniel D. Bastian:
An Adversarial Training Based Machine Learning Approach to Malware Classification under Adversarial Conditions. HICSS 2021: 1-10 - [c7]Kevin Talty, John Stockdale, Nathaniel D. Bastian:
A Sensitivity Analysis of Poisoning and Evasion Attacks in Network Intrusion Detection System Machine Learning Models. MILCOM 2021: 1011-1016 - [c6]Marc Chalé, Nathaniel D. Bastian:
CHALLENGES AND OPPORTUNITIES FOR GENERATIVE METHODS IN THE CYBER DOMAIN. WSC 2021: 1-12 - [c5]Adam D. Cobb, Brian Jalaian, Nathaniel D. Bastian, Stephen Russell:
Robust Decision-Making in the Internet of Battlefield Things Using Bayesian Neural Networks. WSC 2021: 1-12 - 2020
- [c4]Marc Chalé, Nathaniel D. Bastian, Jeffery Weir:
Algorithm selection framework for cyber attack detection. WiseML@WiSec 2020: 37-42 - 2019
- [c3]Paul Maxwell, Elie Alhajjar, Nathaniel D. Bastian:
Intelligent Feature Engineering for Cybersecurity. IEEE BigData 2019: 5005-5011 - [c2]Nathaniel D. Bastian, Christopher B. Fisher, Andrew O. Hall, Brian J. Lunday:
Solving The Army's Cyber Workforce Planning Problem Using Stochastic Optimization and Discrete-Event Simulation Modeling. WSC 2019: 738-749 - 2017
- [c1]Joseph Klobusický, Alexander Murph, Alexander C. Robinson, Nathaniel D. Bastian, Paul M. Griffin, Shravan Kethireddy, Nathan Ryan:
Machine Learning and Statistical Techniques to Predict Sepsis: Unifying Previous Work. CRI 2017
Data and Artifacts
- 2024
- [d1]Nathaniel D. Bastian, David A. Bierbrauer, Morgan McKenzie, Emily Nack:
ACI IoT Network Traffic Dataset 2023. IEEE DataPort, 2024
Informal and Other Publications
- 2024
- [i20]Yuzhou Nie, Yanting Wang, Jinyuan Jia, Michael J. De Lucia, Nathaniel D. Bastian, Wenbo Guo, Dawn Song:
TrojFM: Resource-efficient Backdoor Attacks against Very Large Foundation Models. CoRR abs/2405.16783 (2024) - [i19]Alice Bizzarri, Chung-En Yu, Brian Jalaian, Fabrizio Riguzzi, Nathaniel D. Bastian:
A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI. CoRR abs/2406.00938 (2024) - 2023
- [i18]Taylor Bradley, Elie Alhajjar, Nathaniel D. Bastian:
Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification. CoRR abs/2301.06229 (2023) - [i17]Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno Castro da Silva, Emma Brunskill, Philip S. Thomas:
Off-Policy Evaluation for Action-Dependent Non-Stationary Environments. CoRR abs/2301.10330 (2023) - [i16]Alexander M. Berenbeim, Iain J. Cruickshank, Susmit Jha, Robert H. Thomson, Nathaniel D. Bastian:
Measuring Classification Decision Certainty and Doubt. CoRR abs/2303.14568 (2023) - [i15]Soumyadeep Hore, Jalal Ghadermazi, Diwas Paudel, Ankit Shah, Tapas K. Das, Nathaniel D. Bastian:
Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation. CoRR abs/2305.11039 (2023) - [i14]Iain J. Cruickshank, Jessica Zhu, Nathaniel D. Bastian:
Analysis of Media Writing Style Bias through Text-Embedding Networks. CoRR abs/2305.13098 (2023) - [i13]Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian:
Detecting Unknown Attacks in IoT Environments: An Open Set Classifier for Enhanced Network Intrusion Detection. CoRR abs/2309.07461 (2023) - [i12]Sumit Kumar Jha, Susmit Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Rickard Ewetz, Sandeep Neema:
Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving. CoRR abs/2309.16436 (2023) - [i11]Jingdi Chen, Lei Zhang, Joseph Riem, Gina C. Adam, Nathaniel D. Bastian, Tian Lan:
RIDE: Real-time Intrusion Detection via Explainable Machine Learning Implemented in a Memristor Hardware Architecture. CoRR abs/2311.16018 (2023) - [i10]Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina C. Adam, Nathaniel D. Bastian, Tian Lan:
Real-time Network Intrusion Detection via Decision Transformers. CoRR abs/2312.07696 (2023) - 2022
- [i9]Soumyadeep Hore, Ankit Shah, Nathaniel D. Bastian:
Deep VULMAN: A Deep Reinforcement Learning-Enabled Cyber Vulnerability Management Framework. CoRR abs/2208.02369 (2022) - [i8]Zong-Zhi Lin, Thomas D. Pike, Mark M. Bailey, Nathaniel D. Bastian:
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System. CoRR abs/2211.03933 (2022) - 2021
- [i7]David A. Bierbrauer, Alexander Chang, Will Kritzer, Nathaniel D. Bastian:
Anomaly Detection in Cybersecurity: Unsupervised, Graph-Based and Supervised Learning Methods in Adversarial Environments. CoRR abs/2105.06742 (2021) - 2020
- [i6]Kathleen Kerwin, Nathaniel D. Bastian:
Stacked Generalizations in Imbalanced Fraud Data Sets using Resampling Methods. CoRR abs/2004.01764 (2020) - [i5]Elie Alhajjar, Paul Maxwell, Nathaniel D. Bastian:
Adversarial Machine Learning in Network Intrusion Detection Systems. CoRR abs/2004.11898 (2020) - [i4]Marc Chalé, Nathaniel D. Bastian, Jeffery Weir:
Algorithm Selection Framework for Cyber Attack Detection. CoRR abs/2005.14230 (2020) - [i3]Tyler J. Shipp, Daniel J. Clouse, Michael J. De Lucia, Metin B. Ahiskali, Kai Steverson, Jonathan M. Mullin, Nathaniel D. Bastian:
Advancing the Research and Development of Assured Artificial Intelligence and Machine Learning Capabilities. CoRR abs/2009.13250 (2020) - 2019
- [i2]Timothy J. Kiely, Nathaniel D. Bastian:
The Spatially-Conscious Machine Learning Model. CoRR abs/1902.00562 (2019) - [i1]Sean M. Devine, Nathaniel D. Bastian:
Intelligent Systems Design for Malware Classification Under Adversarial Conditions. CoRR abs/1907.03149 (2019)
Coauthor Index
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