ISAC Privacy: Challenges and Solutions for 6G

2026-05-27

AI Summary

This work addresses the emerging privacy risks in 6G integrated sensing and communication (ISAC), where enhanced performance may inadvertently expose users’ location, behavioral, and physiological information. The study proposes the first privacy classification framework for ISAC data, structured around three dimensions: location-environment, behavior, and physiology. It systematically examines core privacy challenges—including consent, transparency, data ownership, and bystander exposure—across both internal and external deployment scenarios. Leveraging the unique characteristics of millimeter-wave and terahertz bands, the paper conducts a comprehensive privacy risk assessment and formulates a forward-looking privacy-preserving roadmap for 6G ISAC. By identifying key technical and regulatory challenges alongside potential mitigation strategies, this research provides foundational insights and guidance for the privacy-aware design of future 6G networks.

Abstract

Integrated sensing and communication (ISAC) is a promising feature of future communication networks. While spatial sensing can improve network performance and enable external services, it also creates privacy challenges that go beyond the confidentiality of communication content. Future networks using millimeter-wave (mmWave) and sub-terahertz (THz) frequencies may collect or infer detailed information about people, devices, bystanders, passive objects, and environments in a sixth-generation (6G) deployment area. Such sensing can reveal location and environment data, support behavioral profiling such as movement or activity recognition, and, in advanced cases, expose physiological information such as breathing frequency or heart-rate-related data. Thus, the capabilities of spatial sensing must be controlled to satisfy privacy requirements. In this work, we organize privacy-sensitive ISAC data into three sensing levels: location and environment data, behavioral data, and physiological data, and use this classification as the organizing principle throughout the paper. Based on this classification, we discuss internal and external ISAC applications, identify privacy challenges related to consent, transparency, data ownership, profiling, bystander exposure, and sensitive sensing data, review representative solution directions, and outline future research directions for privacy-preserving ISAC.

Problem

• ISAC
• privacy
• 6G
• spatial sensing
• sensitive data

Innovation

• Integrated Sensing and Communication (ISAC)
• 6G privacy
• privacy-sensitive data classification
• mmWave/THz sensing
• privacy-preserving ISAC