# Agents for Agents: An Interrogator-Based Secure Framework for Autonomous Internet of Underwater Things

arXiv: https://arxiv.org/abs/2604.04262 · HTML: https://mlsanity.com/paper/2604.04262/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 21 references that are in the map.
- First posted on arXiv 5 Apr 2026.

## Builds on (most cited first, 6 of 6)

- [EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization](https://mlsanity.com/paper/1404.6264/) (2014)
- [Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach](https://mlsanity.com/paper/2007.09712/) (2020)
- [Multi-Agent Reinforcement Learning for Connected and Automated Vehicles Control: Recent Advancements and Future Prospects](https://mlsanity.com/paper/2312.11084/) (2023)
- [Agentic AI Framework for Individuals with Disabilities and Neurodivergence: A Multi-Agent System for Healthy Eating, Daily Routines, and Inclusive Well-Being](https://mlsanity.com/paper/2511.22737/) (2025)
- [A Blockchain-Monitored Agentic AI Architecture for Trusted Perception-Reasoning-Action Pipelines](https://mlsanity.com/paper/2512.20985/) (2025)
- [FinAgent: An Agentic AI Framework Integrating Personal Finance and Nutrition Planning](https://mlsanity.com/paper/2512.20991/) (2025)

## Abstract (arXiv)

Autonomous underwater vehicles (AUVs) and sensor nodes increasingly support decentralized sensing and coordination in the Internet of Underwater Things (IoUT), yet most deployments rely on static trust once authentication is established, leaving long-duration missions vulnerable to compromised or behaviorally deviating agents. In this paper, an interrogator based structure is presented that incorporates the idea of behavioral trust monitoring into underwater multi-agent operation without interfering with autonomy. Privileged interrogator module is a passive communication metadata analyzer that uses a lightweight transformer model to calculate dynamic trust scores, which are used to authorize the forwarding of mission critical data. Suspicious agents cause proportional monitoring and conditional restrictions, which allow fast containment and maintain network continuity. The evidence of trust is stored in a permissioned blockchain consortium which offers identity management which is not tampered and is decentralized without causing the overhead of public consensus mechanisms. Simulation based analysis shows that the evaluation of the result compares to a relative improvement of 21.7% in the detection accuracy compared to the static trust baselines with limited energy overhead. These findings suggest that behavior driven validation has the capability of reinforcing underwater coordination without compromising scalability and deployment.