LAIRE Publications

LAIRE Publications

Publications

2025

  • Yeung, C., Barkam, H., Zou, Z., Yun, S., Bastian, N. & Imani, M. (2025). Lipschitz-based Robustness Estimation for Hyperdimensional Learning. Frontiers in Artificial Intelligence, 8(1637105), pp. 1-9.
  • Bizzarri, A., Chung-En, Y., Jalaian, B., Riguzzi, F. & Bastian, N. (2025). Neurosymbolic Artificial Intelligence for Network Intrusion Detection Systems: a Survey. Journal of Information Security and Applications, 94(104205), pp. 1-14.
  • Masukawa, R., Yun, S., Jeong, S., Bastian, N. & Imani, M. (2025). TriageHD: A Hyperdimensional Learning-to-Rank Framework for Dynamic Micro-Segmentation in Zero-Trust Network Security. IEEE Access, 13, pp. 136806-136815.
  • Monkam, G., Yan, J. & Bastian, N. (2025). A Forensic Analysis Methodology for Machine Learning Model Poisoning Detection. Security and Privacy, 8(5), e70079, pp. 1-28.
  • Masukawa, R., Yun, S., Jeong, S., Huang, W., Ni, Y., Bryant, I., Bastian, N. & Imani, M. (2025). PacketCLIP: Multi-Modal Embedding of Network Traffic and Language for Cybersecurity Reasoning. Frontiers in Artificial Intelligence, 8(1593944), pp. 1-11.
  • Xiang, Z., Zheng, L., Li, Y., Hong, J., Li, Q., Xie, H., Zhang, J., Xiong, Z., Xie, C., Bastian, N., Yang, C., Song, D. & Li, B. (2025). GuardAgent: Safeguard LLM Agents via Knowledge-Enabled Reasoning. Proceedings of the 2025 ICML Workshop on Computer Use Agents, pp. 1-27.
  • Yeung, C., Zou, Z., Bastian, N. & Imani, M. (2025). Cognitive Map Formation Under Uncertainty via Local Prediction Learning. Intelligent Systems with Applications, 27(200551), pp. 1-11.
  • Farr, D., Ng., L., Cruickshank, I., Manzonelli, N., Clark, N., Starbird, K., Bastian, N. & West, J. (2025). Ensemble-Based Uncertainty Quantification for Reliable Large Language Model Classification in Social Data Applications. IEEE Access, 13, pp. 1-11.
  • Farrukh, Y., Wali, S., Khan, I. & Bastian, N. (2025). Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments. Proceedings of the 2025 IEEE/CVF CVPR Workshop on Computer Vision in the Wild, pp. 1-11.
  • Rivas, E., Saika, S., Bakht, A., Bastian, N. & Shah, S. (2025). Adapting Under Fire: Multi-Agent Reinforcement Learning for Adversarial Drift in Network Security. Proceedings of 2025 International Conference on Security and Cryptography, pp. 1-8.
  • Erbayat, E., Mei, Y., Adam, G., Subramaniam, S., Coffey, S., Bastian, N. & Lan, T. (2025). LAMPS: Learning-based Mobility Planning via Posterior State Inference using Gaussian Cox Process Models. Proceedings of the 2025 IEEE INFOCOM Workshop on Deep Learning for Wireless Communication, Sensing, and Security, pp. 1-8.
  • Ravari, A., Ghoreishi, S., Lan, T., Bastian, N. & Imani, M. (2025). Hybrid Modeling of Heterogeneous Human Teams for Collaborative Decision Processes. Proceedings of Machine Learning Research (7th Annual Conference on Learning for Dynamics & Control), 283, pp. 830-843.
  • Cybenko, G., Lintilhac, P., Ackerman, J. & Bastian, N. (2025). Quantifying Adversarial Risk of Multimodal Foundation Models for Military Applications. Proceedings of the 2025 SPIE DCS Conference on Assurance and Security for AI-enabled Systems (134760J), pp. 134760J-1 – 134760J-18, SPIE Defense + Commercial Sensing (Volume: 13476).
  • Manzonelli, N., Coffey, S. & Bastian, N. (2025). How Private Are Your Chat Adapters? Evaluating the Privacy of LoRA Fine-tuned Large Language Models with Membership Inference Attacks. Proceedings of the 2025 SPIE DCS Conference on Assurance and Security for AI-enabled Systems (1347608), pp. 1347608-1 – 1347608-10, SPIE Defense + Commercial Sensing (Volume: 13476).
  • Beggs, J., Coffey, S., Murphy, J. & Bastian, N. (2025). Resource-Efficient, Self-Adaptive Neuro-Symbolic Artificial Intelligence for the Internet of Battlefield Things. Proceedings of the 2025 SPIE DCS Conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VII (1347308), pp. 1347308-1 – 1347308-12, SPIE Defense + Commercial Sensing (Volume: 13473).
  • Farrukh, Y., Wali, S., Khan, I. & Bastian, N. (2025). XG-NID: Dual-Modality Network Intrusion Detection using a Heterogeneous Graph Neural Network and Large Language Model. Expert Systems with Applications, 287(128089), pp. 1-16.
  • Barzyk, C., Hickson, J., Ochoa, J., Talley, J., Willeke, M., Coffey, S., Pavlik, J. & Bastian, N. (2025). A Generative Artificial Intelligence Methodology for Automated Zero-Shot Data Tagging to Support Tactical Zero Trust Architecture Implementation. Industrial and Systems Engineering Review, 12(2): pp. 83-88.
  • Zou, Z., Bastian, N. & Imani, M. (2025). Metacognitive Modeling with Hyperdimensional Computing. Proceedings of the 2025 SIAM International Conference on Data Mining 2nd Workshop on Metacognitive Predictive of AI Behavior, pp. 1-7.
  • Rifat, S., Sayyed, A., Zhang, M., Bastian, N. & Restuccia, F. (2025). Metacognitive Artificial Intelligence in Vision Foundation Models: Research Challenges. Proceedings of the 2025 SIAM International Conference on Data Mining 2nd Workshop on Metacognitive Predictive of AI Behavior, pp. 1-5.
  • Berenbeim, A. & Bastian, N. (2025). Relevance Scoring as a Feature of Metacognitive Artificial Intelligence. Proceedings of the 2025 SIAM International Conference on Data Mining 2nd Workshop on Metacognitive Predictive of AI Behavior, pp. 1-6.
  • Nelson, Z., Imani, M. & Bastian, N. (2025). Perspectives of Hyperdimensional Computing for Metacognitive Artificial Intelligence. Proceedings of the 2025 SIAM International Conference on Data Mining 2nd Workshop on Metacognitive Predictive of AI Behavior, pp. 1-6.
  • Xiang, Z., Yang, S., Bastian, N. & Li, B. (2025). KnowGuard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning. Proceedings of the 2025 ICLR Workshop on Foundation Models in the Wild, pp. 1-18.
  • Rocca, A., Ayanwale, D., Bond, I., Grooms, E., Corbett, M., Nack, E., Davis, P., Pyke, A. & Bastian, N. (2025). Analyzing the Impact of Improved Situational Awareness on Command and Control System Performance for Decision-Making. Proceedings of the 2025 General Donald R. Keith Memorial Capstone Conference, pp. 79-84.
  • Beggs, J., Coffey, S. & Bastian, N. (2025). Unsupervised Domain Adaptation with Neuro-Symbolic Artificial Intelligence. Proceedings of the 2025 General Donald R. Keith Memorial Capstone Conference, pp. 1-6.
  • Ghadermazi, J., Hore, S., Shah, A. & Bastian, N. (2025). GTAE-IDS: Graph Transformer-based Autoencoder Framework for Real-time Network Intrusion Detection. IEEE Transactions on Information Forensics & Security, 20, pp. 4026-4041.
  • Bierbrauer, D., Coffey, S., Willeke, M., Beggs, J. & Bastian, N. (2025). Data-Efficient Federated Learning for Edge Network Intrusion Detection. Engineering Applications of Artificial Intelligence, 150(110685), pp. 1-11.
  • Ngu, N., Taparia, A., Simari, G., Leiva, M., Corcoran, J., Senanayake, R., Shakarian, P. & Bastian, N. (2025). Multiple Distribution Shift - Aerial (MDS-A): A Dataset for Test-Time Error Detection and Model Adaptation. Proceedings of the 2025 AAAI Spring Symposium on Machine Learning and Knowledge Engineering for Trustworthy Multimodal and Generative AI, pp. 1-5.
  • Shakarian, P., Simari, G. & Bastian, N. (2025). Probabilistic Foundations for Metacognition via Hybrid-AI. Proceedings of the 2025 AAAI Spring Symposium on Machine Learning and Knowledge Engineering for Trustworthy Multimodal and Generative AI, pp. 1-5.
  • Yun, S., Masukawa, R., Chung, W., Na, M., Bastian, N. & Imani, M. (2025). Continuous CNN-based Anomaly Detection on Edge using Efficient Adaptive Knowledge Graph Learning. Proceedings of the 2025 IEEE/ACM Design, Automation and Test in Europe Conference, pp. 1-8.
  • Matejek, B., Gehani, A., Bastian, N., Clouse, D., Kline, B. & Jha, S. (2025). SAFE-NID: Self-Attention with Normalizing-Flow Encodings for Network Intrusion Detection. Transactions on Machine Learning Research, pp. 1-43.
  • Jiang, G., Imani, M., Bastian, N. & Lan, T. (2025). Recovering Reward Functions from Distributed Expert Demonstrations with Maximum-likelihood. Proceedings of the 2025 AAAI Workshop on Cooperative Multi-Agent Systems Decision-Making and Learning: Human-Multi-Agent Cognitive Fusion, pp. 1-8.
  • Yu, F., Zhang, Z., Grob, E., Adam, G., Coffey, S., Bastian, N. & Lan, T. (2025). Look-ahead Robust Network Optimization with Generative State Predictions. Proceedings of the 2025 AAAI Workshop on Artificial Intelligence for Wireless Communications and Networking, pp. 1-5.
  • Bakht, A., Sharma, D., Shah, A. & Bastian, N. (2025). A Reinforcement Learning and Optimization Framework for Crafting Stealthy Poisons through Image Embedding Manipulation. Proceedings of the 2025 AAAI Workshop on Artificial Intelligence for Cyber Security, pp. 1-9.
  • Chen, H., Ni, Y., Huang, W., Liu, Y., Jeong, S., Wen, F., Bastian, N., Latapie, H. & Imani, M. (2025). VLTP: Vision-Language Guided Token Pruning for Task-Oriented Segmentation. Proceedings of the 2025 IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 9335-9345.
  • Roy, A., Cobb, A., Kaur, R., Jha, S., Bastian, N., Cruickshank, I., Berenbeim, A., Thomson, R., Velasquez, A. & Jha, S. (2025). Zero-shot Detection of Out-of-Context Objects Using Foundation Models. Proceedings of the 2025 IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 9168-9177.
  • Hore, S., Ghadermazi, J., Paudel, D., Shah, A., Das, T. & Bastian, N. (2025). Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation. ACM Transactions on Privacy and Security, 28(2), Article No. 15, pp. 1-33.
  • Berenbeim, A., Cobb, A., Roy, A., Jha, S. & Bastian, N. (2025). Applications of Certainty Scoring for Machine Learning Classification and Out-of-Distribution Detection. ACM Transactions on Probabilistic Machine Learning. Just Accepted, pp. 1-34.
  • Rajkumardheivanayahi, P., Berry, R., Costagliola, N., Fiondella, L., Bastian, N. & Kul, G. (2025). Explainability of Network Intrusion Detection using Transformers: A Packet-Level Approach. IEEE Access, 13, pp. 5154-5174.
  • Broggi, A., Baye, G., Silva, P., Costagliola, N., Bastian, N., Fiondella, L. & Kul, G. (2025).  varMax: Uncertainty and Novelty Management in Deep Neural Networks. Proceedings of the 2025 Hawaii International Conference on System Sciences, pp. 7514-7523.
  • Bakht, A., Shah, A. & Bastian, N. (2025). Towards Attribution in Network Attacks: A Deep Learning-Based Robust Framework for Intrusion Detection and Adversarial Toolchain Identification. Proceedings of the 2025 Hawaii International Conference on System Sciences, pp. 383-392.