Joint Accuracy and Confidentiality in Semantic-Aware Secure Remote Reconstruction

2026-04-30

AI Summary

This study addresses the fundamental trade-off between reconstruction accuracy and confidentiality in wireless remote reconfiguration systems. To this end, it introduces a novel metric—Confidential Reconstruction Accuracy (CRA)—which uniquely models successful reconstruction at the legitimate receiver and failure at the eavesdropper as a joint event, thereby exposing the limitations of conventional marginal analysis. By incorporating randomized stationary policies, the work establishes a three-dimensional steady-state analytical framework and derives closed-form expressions for both the long-term average CRA and the optimal transmission probability. The analysis reveals that transmission frequency and channel quality exert non-monotonic effects on joint performance and demonstrates that enhancing only the legitimate channel quality may be ineffective under strong eavesdropping conditions. To mitigate this, the paper proposes a geofencing-based spatial security boundary mechanism.

Abstract

In this paper, we consider remote reconstruction over wireless networks when simultaneous accuracy at the legitimate receiver and confidentiality against eavesdropping are required. These two objectives are often treated separately, even though they arise from the same update process and are marginals of a joint reconstruction event. This paper introduces confidential reconstruction accuracy (CRA), a metric to capture the joint event in which the legitimate receiver reconstructs correctly while the eavesdropper fails. Under randomized stationary policies, we develop a three-dimensional stationary analysis and derive closed-form expressions for the long-term average CRA and the optimal transmission probability. The results show that conventional marginal analysis can misidentify the optimal policy and misestimate the achievable simultaneous accuracy-confidentiality performance. They also reveal nontrivial behaviors: more frequent transmissions or better legitimate channels do not necessarily improve joint accurate and confidential reconstruction, and when the eavesdropping channel is strong, improving the legitimate channel alone may be insufficient. Finally, the framework induces the spatial safety boundary in a geofencing setting for secure remote reconstruction.

Problem

• semantic-aware reconstruction
• accuracy
• confidentiality
• eavesdropping
• wireless networks

Innovation

• Confidential Reconstruction Accuracy
• joint accuracy-confidentiality
• secure remote reconstruction
• stationary policy analysis
• spatial safety boundary