WiFi Networks Can Identify Individuals With 99.5% Accuracy, Researchers Warn of Privacy Risks

Your WiFi router could reveal more than your personal information. The scariest part could be knowing that it can be used for surveillance in places where most people pass by.

Researchers at the Karlsruhe Institute of Technology (KIT) in Germany have found that standard WiFi networks can identify individuals with surprising accuracy using advanced signal analysis and machine learning.

The study suggests that everyday wireless systems may unintentionally expose personal identity patterns, raising concerns about passive surveillance in public spaces.

Beamforming Data Exposes Hidden User Information

The research focuses on WiFi beamforming, a technology introduced with WiFi 5 that improves signal direction by targeting devices more efficiently. To support this process, connected devices send beamforming feedback information (BFI) back to routers.

The findings indicate that people can potentially be recognized without actively connecting their devices to a network.

According to the study, this feedback data is often unencrypted and can be accessed and analyzed without specialized hardware or direct network access.

Researchers found that these signal patterns contain unique behavioral markers that can be used to infer identity-related characteristics.

Machine Learning Achieves Near-Perfect Identification

The KIT team trained machine learning models using WiFi data collected from nearly 200 participants walking through a controlled signal environment. The dataset included multiple viewing angles and combined both beamforming feedback information (BFI) and channel state information (CSI).

According to Gizmodo, the results showed that the system achieved an accuracy of up to 99.5% in identifying individuals using BFI data alone.

Even CSI-based methods reached accuracy levels of 82.4%. Once trained, the system could identify individuals within seconds, demonstrating how quickly WiFi-based recognition can operate.

WiFi Sensing Turns Signals Into Behavioral Data

WiFi sensing works by analyzing how radio waves interact with people and objects in an environment. As signals bounce, scatter, and absorb, they create patterns that can be used to reconstruct movement and environmental changes.

KIT professor Thorsten Strufe explained in a press release that the process is similar to how a camera forms an image, except it uses radio waves instead of light. This enables WiFi systems to detect presence, movement, and behavioral patterns without relying on optical sensors.

Privacy Risks and Surveillance Concerns Increase

Researchers warn that WiFi sensing could turn ordinary routers into powerful surveillance tools. Because feedback data is often unencrypted, it may be possible for third parties within range to intercept and analyze it.

Co-author Julian Todt noted that individuals passing through public spaces such as cafés could potentially be tracked and identified over time.

The research team is urging the IEEE to strengthen privacy protections in the upcoming 802.11bf standard, which will govern WiFi sensing technologies. They recommend stronger encryption and stricter controls on feedback data to reduce the risk of misuse.