A Novel Framework for Transmitter Privacy in Integrated Sensing and Communication

• URL: http://arxiv.org/abs/2604.16068v1
• Date: Fri, 17 Apr 2026 13:52:18 GMT
• Title: A Novel Framework for Transmitter Privacy in Integrated Sensing and Communication
• Abstract summary: An unintended sensing node may exploit the shared radio waveform to infer transmitter-related information even when the communication payload remains secure.<n>This paper investigates transmitter privacy, defined as limiting unauthorized of transmitter-related information through channel estimation.
• Score: 30.11438480964021
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: ISAC systems introduce new privacy risks because an unintended sensing node may exploit the shared radio waveform to infer transmitter-related information even when the communication payload remains secure. This paper investigates transmitter privacy, defined as limiting unauthorized inference of transmitter-related information through channel estimation, in a RIS-aided multi-antenna wireless system with a transmitter, a legitimate receiver, a malicious sensor, and a RIS. The malicious sensor is assumed to estimate the transmitter--sensor channel, and the resulting channel state information can then support unauthorized sensing, inference, or related signal processing. To mitigate this threat, we consider a privacy-oriented design in which the transmitter adopts superposition-based signaling with a message signal and transmit-side artificial noise, while the RIS shapes the propagation environment in a privacy-aware manner. The channel-estimation performance at the malicious sensor is first analyzed under imperfect prior knowledge, and both the true and predicted mean-square-error expressions are derived. Based on this analysis, we formulate a joint active--passive beamforming design problem that maximizes the malicious sensor's predicted channel-estimation error subject to a communication quality-of-service constraint, a transmit-power budget, and the unit-modulus constraints of the RIS. The resulting non-convex problem is handled through a numerically efficient alternating-optimization framework based on an augmented Lagrangian reformulation. Numerical results show that RIS-assisted propagation shaping can substantially degrade unauthorized channel estimation relative to the non-RIS case while preserving reliable communication, and further show that the privacy gains also improve a more direct sensing metric, namely the malicious sensor's angle-of-arrival estimation accuracy.

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