Publications

[CONF] L. Niu, S. Cheng, B. Ramasubramanian, L. Bushnell, A. Clark, R. Poovendran, Submodular Swarm Assignment for Multi-Agent Systems under Linear Temporal Logic Contraints, Proc. IEEE Conference on Decision and Control (IEEE CDC), 2025. 

[JRNL] K. Balasubramanian, A. G. Baragur, D. Donadel, D. Sahabandu, A. Brighente, B. Ramasubramanian, M. Conti, R. Poovendran, CANLP: Intrusion Detection for Controller Area Networks using Natural Language Processing and Embedded Machine Learning, IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2025. (DOI: https://ieeexplore.ieee.org/document/11114906)

[CONF] Y. Li, X. Yue, Z. Xu, F. Jiang, L. Niu, B. Y. Lin, B. Ramasubramanian, R. Poovendran, Small Models Struggle to Learn from Strong Reasoners, Findings of the Annual Meeting of the Association for Computational Linguistics (ACL), 2025. [Paper] [arXiv]

[CONF] D. Donadel, K. Balasubramanian, A. Brighente, B. Ramasubramanian, M. Conti, R. Poovendran, CANTXSec: A Deterministic Intrusion Detection and Prevention System for CAN Bus Monitoring ECU Activations, International Conference on Applied Cryptography and Network Security (ACNS), 2025. [Paper] [arXiv]

[JRNL] S. Cheng, L. Niu, B. Ramasubramanian, A. Clark, R. Poovendran, Modeling and Designing Non-Pharmaceutical Interventions in Epidemics: A Submodular Approach, IEEE Control System Letters (L-CSS), Vol. 8, 2024. (DOI: 10.1109/LCSYS.2024.3507641)

[CONF] L. Niu, B. Ramasubramanian, A. Clark, R. Poovendran, Sampling and Quantization-Aware Control Barrier Functions for Safety-Critical Control of Cyber-Physical Systems, IEEE Conference on Decision and Control (CDC), 2024. [Paper]

[CONF] Y. Li, Z. Xu, F. Jiang, L. Niu, D. Sahabandu, B. Ramasubramanian, R. Poovendran, CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models, Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024. [Paper] [arXiv] 

[CONF] M. Faraz Karim, Y. Deng, L. Niu, B. Ramasubramanian, M. Alexiou, D. Sahabandu, R. Poovendran, S. Mertoguno, Rapid Autonomy Transfer in Reinforcement Learning with a Single Pretrained Critic, IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2024. [Paper]

[CONF] L. Niu, H. Zhang, D. Sahabandu, B. Ramasubramanian, A. Clark, R. Poovendran, Who is Responsible? Explaining Safety Violations in Multi-Agent Cyber Physical Systems, IEEE International Conference on Assured Autonomy (ICAA), 2024. [Paper]

[PREPRINT] D. Sahabandu, B. Ramasubramanian, M. Alexiou, J. Sukarno Mertoguno, L. Bushnell, R. Poovendran, A Method for Fast Autonomy Transfer in Reinforcement Learning, 2024. [arXiv]

[CONF] F. Jiang, Z. Xu, L. Niu, Z. Xiang, B. Ramasubramanian, B. Li, R. Poovendran, ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs, Annual Conference of the Association for Computational Linguistics (ACL), 2024. [Paper] [arXiv][Media Features: Inc.com, PCGamer, Tom's Hardware, Twitter] [Acceptance rate ~21%]

[CONF] A. Al Maruf, L. Niu, B. Li, B. Ramasubramanian, A. Clark, R. Poovendran, Risk-Aware Distributed Multi-Agent Reinforcement Learning, American Control Conference (ACC), 2024. [arXiv]

[CONF] A. Rajabi, R. Pimple, A. Janardhanan, S. Asokraj, B. Ramasubramanian, R. Poovendran, POSTER: Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization, ACM ASIA Conference on Computer and Communications Security (AsiaCCS), 2024. [Paper]

[CONF] D. Sahabandu, X. Xu, A. Rajabi, L. Niu, B. Ramasubramanian, B. Li, R. Poovendran, POSTER: Game of Trojans: Adaptive Adversaries Against Output-Based Trojaned Model Detectors, ACM ASIA Conference on Computer and Communications Security (AsiaCCS), 2024. [Paper]

[CONF] Q. Lu, B. Ramasubramanian, R. Poovendran, EDC: Efficient and Effective Dialog Comprehension for Dialog State Tracking, Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024. [Paper] [Acceptance rate ~23%]

[PREPRINT] D. Sahabandu, X. Xu, A. Rajabi, L. Niu, B. Ramasubramanian, B. Li, R. Poovendran, Game of Trojans: Adaptive Adversaries Against Output-Based Trojaned Model Detectors, 2024. [arXiv]

[PREPRINT] A. Rajabi, R. Pimple, A. Janardhanan, S. Asokraj, B. Ramasubramanian, R. Poovendran, Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization, 2024. [arXiv]

[CONF] Z. Xiang F. Jiang, Z. Xiong, B. Ramasubramanian, R. Poovendran, B. Li, BadChain: backdoor Chain-of-Thought Prompting for Large Language Models, International Conference on Learning Representations (ICLR), 2024. [Paper] [Acceptance rate ~31%]

[CONF] K. Balasubramanian, A. Gowda Baragur, D. Donadel, D. Sahabandu, A. Brighente, B. Ramasubramanian, M. Conti, R. Poovendran, CANLP: NLP-Based Intrusion Detection System for CAN, ACM Symposium on Applied Computing (ACM SAC), Cyber Physical Systems Track, 2024. [Paper] [Acceptance rate ~33%]

[CONF] J. Jia, Z. Yuan, D. Sahabandu, L. Niu, A. Rajabi, B. Ramasubramanian, B. Li, R. Poovendran, FedGame: A Game-Theoretic Defense Against Backdoor Attacks on Federated Learning, Conference on Advances in Neural Information Processing Systems (NeurIPS), 2023. [Paper] [Acceptance rate ~26%]

[PRESENT] Z. Xiang F. Jiang, Z. Xiong, B. Ramasubramanian, R. Poovendran, B. Li, BadChain: backdoor Chain-of-Thought Prompting for Large Language Models, NeurIPS 2023 Workshop on Backdoors in Deep Learning- The Good, The Bad, and The Ugly. 

[CONF] A. Rajabi, S. Asokraj, F. Jiang, L. Niu, B. Ramasubramanian, J. Ritcey, R. Poovendran, MDTD: A Multi-Domain Trojan Detector for Deep Neural Networks, ACM Conference on Computer and Communications Security (CCS), 2023. [Paper] [arXiv] [Acceptance rate ~20%]

[CONF] A. Al Maruf, L. Niu, B. Ramasubramanian, A. Clark, R. Poovendran, Learning Dissemination Strategies for External Sources in Opinion Dynamic Models with Cognitive Biases, International Joint Conference on Artificial Intelligence (IJCAI), 2023. [Paper] [Preprint] [Acceptance rate ~15%] 

[PRESENT] T. Roque, M. Le, D. Danis, B. Ramasubramanian, Risk-Aware Decision Making for Autonomous Driving with Theory of Mind, SIAM Conference on Control and its Applications (SIAM CT), 2023. 

[PRESENT] D. Danis, P. Parmacek, D. Dunajsky, B. Ramasubramanian, Multi-Agent Reinforcement Learning with Prospect Theory, SIAM Conference on Control and its Applications (SIAM CT), 2023. 

[CONF] D. Danis, P. Parmacek, D. Dunajsky, B. Ramasubramanian, Multi-Agent Reinforcement Learning with Prospect Theory, SIAM Conference on Control and its Applications (SIAM CT), 2023. [Paper]

[CONF] A. Rajabi, B. Ramasubramanian, D. Sahabandu, L. Niu, R. Poovendran, LDL: A Defense for Light-Weight Membership Inference Attacks, ACM ASIA Conference on Computer and Communications Security (AsiaCCS), 2023. [Paper] [arXiv] [Acceptance rate ~17%]

[CONF] A. Lotto, V. Singh, B. Ramasubramanian, A. Brighente, M. Conti, R. Poovendran, BARON: Base-Station Authentication through Core Network for Mobility Management in 5G Networks, ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec), 2023. [Paper] [Acceptance rate ~25%]

[CONF] A. Al Maruf, L. Niu, B. Ramasubramanian, A. Clark, R. Poovendran, Cognitive Bias-Aware Dissemination Strategies for Opinion Dynamics with External Information Sources, International Conference on Autonomous Agents and Multi Agent Systems (AAMAS), 2023. [Paper] [Poster Presentation; Acceptance rate ~22%] 

[JRNL] L. Niu, B. Ramasubramanian, A. Clark, R. Poovendran, Robust Satisfaction of Metric Interval Temporal Logic Objectives in Adversarial Environments, MDPI Games; Special Issue on Game-Theoretic Analysis of Network Security and Privacy (Ed. Prof. Y. Vorobeychik), Vol. 14, Issue 2, April 2023 (DOI: https://doi.org/10.3390/g14020030). [COVER PAGE Feature]

[CONF] A. Rajabi, B. Ramasubramanian, A. Al Maruf, R. Poovendran, Privacy-Preserving Reinforcement Learning Beyond Expectation, IEEE Conference on Decision and Control (CDC), 2022. [Paper] [arXiv]

[PREPRINT] D. Sahabandu, A. Rajabi, L. Niu, B. Li, B. Ramasubramanian, R. Poovendran, Game of Trojans: A Submodular Byzantine Approach, 2022. [arXiv]

[PREPRINT] A. Rajabi, B. Ramasubramanian, R. Poovendran, Trojan Horse Training for Breaking Defenses Against Backdoor Attacks, 2022. [arXiv]

[PREPRINT] B. Xiao, B. Ramasubramanian, R. Poovendran, Shaping Advice in Deep Reinforcement Learning, 2022. [arXiv]

[CONF] B. Xiao, B. Ramasubramanian, R. Poovendran, Agent-Temporal Attention for Reward Redistribution in Episodic Multi-Agent Reinforcement Learning, International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2022. [Paper] [arXiv] [Oral Presentation; Acceptance rate 26%] 

[JRNL] B. Ramasubramanian, M. A. Rajan, M. G. Chandra, R. Cleaveland, S. I. Marcus, Resilience to Denial-of-Service Attacks : A Structured Systems Approach, European Journal on Control, Vol. 63, pp. 61-69, January 2022 (DOI: https://doi.org/10.1016/j.ejcon.2021.09.005). [arXiv]

[JRNL] B. Ramasubramanian, L. Niu, A. Clark, L. Bushnell, R. Poovendran,  Secure Control in Partially Observable Environments to Satisfy LTL Specifications, IEEE Transactions on Automatic Control, Vol. 66, No. 12, pp. 5665-5679, 2021 (DOI: 10.1109/TAC.2020.3039484). [arXiv]

[CONF] B. Ramasubramanian, L. Niu, A. Clark, R. Poovendran, Reinforcement Learning Beyond Expectation, Proceedings of the IEEE Conference on Decision and Control, 2021. [Paper] [arXiv]