Advanced Techniques for Preventing Thermal Imaging Attacks

Thermal cameras can be used to detect user input on interfaces, such as touchscreens, keyboards, and PIN pads, by recording the heat traces left by the users’ fingers after interaction (e.g., typing a message or entering a PIN) and using them to reconstruct the input. While previous work mitigated the thermal attacks by complicating input or distorting heat traces, our research is the first to propose preventing thermal attack using deep learning (DL) techniques to prevent malicious use of thermal cameras. Our DL models detect interfaces in the thermal camera feed and then obfuscate heat traces on them. Our preliminary findings show that the proposed framework can detect interfaces and eliminate authentication information from thermal images. At the same time, our methods still reveal if an interface has been interacted with. Thus, our approach improves security without impacting the utility of the thermal camera.