Joint Accuracy and Confidentiality in Semantic-Aware Secure Remote Reconstruction
For wireless communication systems requiring both accuracy and security, this work provides a unified framework that corrects limitations of separate marginal analyses.
This paper introduces a joint metric, confidential reconstruction accuracy (CRA), to simultaneously evaluate reconstruction accuracy at a legitimate receiver and confidentiality against eavesdropping in wireless remote reconstruction. The analysis reveals that conventional marginal approaches can misidentify optimal policies and that increasing transmission frequency or improving legitimate channels does not always enhance joint performance.
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.