Author

E. C. Pinto

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Review Open access Aug 2026

From static tasks to dynamic reasoning: a characterization framework and study of large language models in next-generation cybersecurity automation

This work surveys recent LLM-based systems across seven core domains and identifies the need for privacy-aware deployment, timely retrieval and knowledge maintenance for emerging threats, process-level evaluation tied to measurable security outcomes, and human oversight within controlled and hybrid automation workflows...

Hanxin Yu, Shahrear Iqbal, E. C. Pinto et al. · International Journal of Inf... · 0 citations

Conference Jul 2026

Can LLM Agents Replace Reinforcement Learning Agents in Cyber Defence Automation: A Case Study Using the DARPA CAGE-2 Challenge

As cyber attacks grow more sophisticated, defenders need autonomous systems that are fast, adaptable, and explainable. Over the last decade, various strategies have been proposed for automated cyber defence (as opposed to static rule-based or signature-based), including those based on reinforcement learning (RL). Resea...

Arijit Diganto, S. Lohrasbi, Euclides Carlos Pinto et al. · International Conference on... · 0 citations

2026

Cyber Task Automation With Knowledge-Infused Reinforcement Learning and LLM-Guided Policies

As cyber threats continue to evolve, there is a need for Autonomous Cyber Defense (ACD) strategies capable of fast and context-aware responses. Reinforcement learning (RL) has shown promise in automating cyber defense by exploring and learning effective countermeasures. However, RL often struggles with sparse reward si...

Md. Shamim Towhid, Shahrear Iqbal, E. C. Pinto et al. · IEEE Transactions on Network... · 0 citations