A Dual Belief-Driven Bayesian-Stackelberg Framework for Low-Complexity and Secure Near-Field ISAC Systems

Fuente: arXiv
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Main Authors: Iqbal, Mehzabien, Javaid, Ahmad Y
Format: Preprint
Published: 2026
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author Iqbal, Mehzabien
Javaid, Ahmad Y
author_facet Iqbal, Mehzabien
Javaid, Ahmad Y
contents Ensuring robust security in near-field Integrated Sensing and Communication (ISAC) systems remains a critical challenge due to dynamic channel conditions, multi-eavesdropper threats, and the high computational burden of real-time optimization at mmWave and THz frequencies. To address these challenges, this paper introduces a novel Bayesian-Stackelberg framework that jointly optimizes sensing, beamforming, and communication. The dual-algorithm design integrates (i) Adaptive Hybrid Node Role Switching between secure transmission and cooperative jamming (ii) Belief-Driven Sensing and Beamforming for confidence based resource allocation. The proposed unified framework significantly improves robustness against attacks while preserving linear computational complexity. Simulation results across carrier frequencies ranging from 28 to 410 GHz demonstrate that the method achieves up to a 35% increase in secrecy rates and a success rate exceeding 98%, outperforming conventional communication systems with minimal runtime overhead. These findings underscore the scalability of belief-driven ISAC security solutions for low-complexity deployment in next generation communications.
format Preprint
id arxiv_https___arxiv_org_abs_2602_09754
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Dual Belief-Driven Bayesian-Stackelberg Framework for Low-Complexity and Secure Near-Field ISAC Systems
Iqbal, Mehzabien
Javaid, Ahmad Y
Signal Processing
Ensuring robust security in near-field Integrated Sensing and Communication (ISAC) systems remains a critical challenge due to dynamic channel conditions, multi-eavesdropper threats, and the high computational burden of real-time optimization at mmWave and THz frequencies. To address these challenges, this paper introduces a novel Bayesian-Stackelberg framework that jointly optimizes sensing, beamforming, and communication. The dual-algorithm design integrates (i) Adaptive Hybrid Node Role Switching between secure transmission and cooperative jamming (ii) Belief-Driven Sensing and Beamforming for confidence based resource allocation. The proposed unified framework significantly improves robustness against attacks while preserving linear computational complexity. Simulation results across carrier frequencies ranging from 28 to 410 GHz demonstrate that the method achieves up to a 35% increase in secrecy rates and a success rate exceeding 98%, outperforming conventional communication systems with minimal runtime overhead. These findings underscore the scalability of belief-driven ISAC security solutions for low-complexity deployment in next generation communications.
title A Dual Belief-Driven Bayesian-Stackelberg Framework for Low-Complexity and Secure Near-Field ISAC Systems
topic Signal Processing
url https://arxiv.org/abs/2602.09754