A Survey of Wireless Sensing Security from a Role-Based View: Victim, Weapon, and Shield

TL;DR

This article addresses the security challenges of wireless sensing by proposing a novel, role-based framework that classifies research into three categories: wireless systems as victims, wireless signals as weapons, and wireless signals as shields. Based on an analysis of over 200 publications from 2020–2024, the authors establish the Awesome-WS-Security database and a 3-level taxonomy (3 main categories, 10 secondary, 24 tertiary classifications) to unify diverse security topics across mmWave, WiFi, acoustic sensing, and ISAC contexts. The survey details attacks on sensing targets, sources, and channels; defenses at active and passive layers; and security applications where wireless signals enable biometric authentication, device authenticity, and privacy protection. It also provides quantitative insights into research trends, identifies cross-domain attack models and foundation-model-enabled defenses, and suggests future directions for multi-level collaboration, intelligent defense, preventive active defense, and cognitive security. Overall, the work offers a structured lens for understanding wireless sensing security’s landscape, guiding both newcomers and researchers toward coherent, cross-domain defenses and applications.

Abstract

Wireless sensing technology has become prevalent in healthcare, smart homes, and autonomous driving due to its non-contact operation, penetration capabilities, and cost-effectiveness. As its applications expand, the technology faces mounting security challenges: sensing systems can be attack targets, signals can be weaponized, or signals can function as security shields. Despite these security concerns significantly impacting the technology's development, a systematic review remains lacking. This paper presents the first comprehensive survey of wireless sensing security through a role-based perspective. Analyzing over 200 publications from 2020-2024, we propose a novel classification framework that systematically categorizes existing research into three main classes: (1) wireless systems as victims of attacks, (2) wireless signals as weapons for attacks, and (3) wireless signals as shields for security applications. This role-based classification method is not only intuitive and easy to understand, but also reflects the essential connection between wireless signals and security issues. Through systematic literature review and quantitative analysis, this paper outlines a panoramic view of wireless sensing security, revealing key technological trends and innovation opportunities, thereby helping to promote the development of this field. Project page: \url{https://github.com/Intelligent-Perception-Lab/Awesome-WS-Security}.

Figures (14)

• Figure 1: Wireless sensing security can be categorized into three classes based on the role wireless signals play: Victims, Weapons and Shields.
• Figure 2: Overall structure of the paper.
• Figure 3: A framework diagram for conducting attacks from the target's perspective.
• Figure 4: Overview of attacks on wireless sensing sources. The top row illustrates three primary attack types: jamming attacks that overwhelm the receiver with high-power interference, spoofing attacks that inject false signals to deceive signal processing, and adversarial attacks that introduce subtle perturbations.
• Figure 5: A unified attack framework for wireless sensing systems. Attackers can target three perspectives (source, target, channel) across four key dimensions (range, Doppler, angle, time/frequency).