Nathaniel D. Bastian

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 60

Top Topics

Intrusion Detection

Machine Learning

Network Intrusion

Symbolic Reasoning

Top Venues

Expert Syst. Appl.

Publications

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 (2024)
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) (2024)
Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian
AIS-NIDS: An intelligent and self-sustaining network intrusion detection system. Comput. Secur. 144 (2024)
Alice Bizzarri, Chung-En Yu, Brian Jalaian, Fabrizio Riguzzi, Nathaniel D. Bastian
A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI. CoRR (2024)
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)
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 (2024)
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 (2024)
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 (2023)
Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina C. Adam, Nathaniel D. Bastian, Tian Lan
Real-time Network Intrusion Detection via Decision Transformers. CoRR (2023)
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 (2023)
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)
Taylor Bradley, Elie Alhajjar, Nathaniel D. Bastian
Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification. ICAA (2023)
Brian Jalaian, Nathaniel D. Bastian
Neurosymbolic AI in Cybersecurity: Bridging Pattern Recognition and Symbolic Reasoning. MILCOM (2023)
Soumyadeep Hore, Ankit Shah, Nathaniel D. Bastian
Deep VULMAN: A deep reinforcement learning-enabled cyber vulnerability management framework. Expert Syst. Appl. 221 (2023)
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)
Joshua A. Wong, Alexander M. Berenbeim, David A. Bierbrauer, Nathaniel D. Bastian
Uncertainty-Quantified, Robust Deep Learning for Network Intrusion Detection. WSC (2023)
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 (2023)
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 (2023)
Iain J. Cruickshank, Jessica Zhu, Nathaniel D. Bastian
Analysis of Media Writing Style Bias through Text-Embedding Networks. CoRR (2023)
Galamo Monkam, Michael J. De Lucia, Nathaniel D. Bastian
Preprocessing Network Traffic using Topological Data Analysis for Data Poisoning Detection. DSC (2023)
Taylor Bradley, Elie Alhajjar, Nathaniel D. Bastian
Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification. CoRR (2023)
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)
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 (2023)
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)
Kelson J. McCollum, Nathaniel D. Bastian, Johannes O. Royset
Towards Robust Learning using Diametrical Risk Minimization for Network Intrusion Detection. DSC (2023)
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) (2023)
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 (2023)
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)
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)
Alexander M. Berenbeim, Iain J. Cruickshank, Susmit Jha, Robert H. Thomson, Nathaniel D. Bastian
Measuring Classification Decision Certainty and Doubt. CoRR (2023)
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)
John H. Smith, Nathaniel D. Bastian
A ranked solution for social media fact checking using epidemic spread modeling. Inf. Sci. 589 (2022)
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 (2022)
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)
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)
Soumyadeep Hore, Ankit Shah, Nathaniel D. Bastian
Deep VULMAN: A Deep Reinforcement Learning-Enabled Cyber Vulnerability Management Framework. CoRR (2022)
Zong-Zhi Lin, Thomas D. Pike, Mark M. Bailey, Nathaniel D. Bastian
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System. CoRR (2022)
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)
Marc Chalé, Nathaniel D. Bastian
CHALLENGES AND OPPORTUNITIES FOR GENERATIVE METHODS IN THE CYBER DOMAIN. WSC (2021)
Elie Alhajjar, Paul Maxwell, Nathaniel D. Bastian
Adversarial machine learning in Network Intrusion Detection Systems. Expert Syst. Appl. 186 (2021)
Madeleine Schneider, David Aspinall, Nathaniel D. Bastian
Evaluating Model Robustness to Adversarial Samples in Network Intrusion Detection. IEEE BigData (2021)
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)
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)
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 (2021)
Sean M. Devine, Nathaniel D. Bastian
An Adversarial Training Based Machine Learning Approach to Malware Classification under Adversarial Conditions. HICSS (2021)
Kathleen Kerwin, Nathaniel D. Bastian
Stacked Generalizations in Imbalanced Fraud Data Sets using Resampling Methods. CoRR (2020)
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 (2020)
Marc Chalé, Nathaniel D. Bastian, Jeffery Weir
Algorithm selection framework for cyber attack detection. WiseML@WiSec (2020)
Marc Chalé, Nathaniel D. Bastian, Jeffery Weir
Algorithm Selection Framework for Cyber Attack Detection. CoRR (2020)
Elie Alhajjar, Paul Maxwell, Nathaniel D. Bastian
Adversarial Machine Learning in Network Intrusion Detection Systems. CoRR (2020)
Timothy J. Kiely, Nathaniel D. Bastian
The spatially conscious machine learning model. Stat. Anal. Data Min. 13 (1) (2020)
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)
Sean M. Devine, Nathaniel D. Bastian
Intelligent Systems Design for Malware Classification Under Adversarial Conditions. CoRR (2019)
Paul Maxwell, Elie Alhajjar, Nathaniel D. Bastian
Intelligent Feature Engineering for Cybersecurity. IEEE BigData (2019)
Timothy J. Kiely, Nathaniel D. Bastian
The Spatially-Conscious Machine Learning Model. CoRR (2019)
Sharan Srinivas, Mohammadmahdi Alizadeh, Nathaniel D. Bastian
Optimizing Student Team and Job Assignments for the Holy Family Academy. Interfaces 47 (2) (2017)
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)
Tulasi K. Paradarami, Nathaniel D. Bastian, Jennifer L. Wightman
A hybrid recommender system using artificial neural networks. Expert Syst. Appl. 83 (2017)
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 (2016)
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) (2016)
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) (2015)
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) (2015)
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) (2013)