This paper introduces reconCTI, a Python-based command-line tool designed to proactively search for sensitive data leaks on both surface and dark web platforms to aid in early risk identification.

This paper reviews advanced AI-based solutions, specifically combining LLMs and RL, to create dynamic and cost-effective network and device-level cyber deception strategies for contested environments.

This study analyzed eye-tracking data in a simulated military environment, finding that multimodal adaptive decision support tools significantly improve mission performance compared to visual-only too…

A lightweight sensor-driven Lévy walk controller is presented for efficient autonomous exploration of minimal-sensing, resource-constrained nano-UAVs.

This paper systematically analyzes 48 studies on perception attacks against autonomous vehicles, revealing that the increasing reliance on multi-sensor fusion creates new, complex vulnerabilities that…

The paper demonstrates that soft fusion in multi-warden covert communication has structural limits, showing that the Fusion Center gains no significant detection advantage from randomizing the number…

This paper evaluates the assumption that decoy placement is possible for all MITRE ATT&CK v18.1 techniques and introduces a rubric for infrastructure deception.

TriSweep proposes a novel four-drone swarm framework for autonomous, standoff electromagnetic side-channel analysis, achieving high key rank recovery even with significant signal degradation and jitte…

The ACTING platform addresses the need for interoperable cyber-range training by providing a structured language (EDL-FG) for scenario description and automated evaluation mechanisms for complex, mult…

The paper proposes an uncertainty-aware, decentralized fusion layer for multi-UAV systems that significantly improves 3D localization robustness by incorporating neighbor constraints and handling faul…

The paper analyzes robust covert wireless communication under bounded uncertainty, demonstrating that the adverse conditions governing reliability and covertness are distinct, thus requiring a conflic…

The paper demonstrates a coordinated, cross-modal spoofing attack that successfully deceives state-of-the-art multi-sensor fusion systems in autonomous vehicles by making multiple sensors agree on a f…

SentinelAgent introduces a formal framework, the Intent-Preserving Delegation Protocol (IPDP), to secure federal multi-agent AI systems by verifying complex delegation chains against seven properties,…

This paper proposes a multi-modal reconstruction framework using outdated DEMs as geometric priors for image-based 3D terrain mapping in wildfire-prone regions, improving accuracy and efficiency.

This paper proposes a cloud-edge-end collaborative defense framework to secure UAV swarms against various threats like GPS spoofing and multi-hop intrusions, demonstrating its effectiveness through ex…

This paper proposes ASMR, a framework for automatically generating compact and informative schemas from historical ship maintenance reports using two specialized agents.

A neural network called DMSNet is proposed for multi-target sensing in multi-band integrated sensing and communication systems, improving accuracy, reducing errors, and decreasing runtime.