Triboelectric sensor-empowered intelligent mouse combined with machine learning technology strides toward a computer security system

The computer mouse is one of the most common tools used for human-machine interfacing. The human behavior studying by click operation using an intelligent mouse and related security identification of computers remains a great challenge. Here, we develop an intelligent mouse embedded with a contact-separation adaptable triboelectric sensor based on the intrinsic mouse button click operation. With the unique characteristics of different individuals who use the intelligent mouse and machine learning algorithms, an identity recognition system was designed. Through processes such as signal processing, feature extraction, and model training, high-accuracy (98.4%) identification of different individuals based on the signals from the embedded triboelectric sensor in the mouse was achieved. In addition, we have developed a security alarm system for detecting unauthorized users operating the computer, and successfully validated the practicality of this system. A system for monitoring user behaviors while operating the computer has been designed to meet the monitoring needs of user computer usage states. This system can monitor users' gaming, working, or studying states, while effectively protecting users' privacy. In general, this work reveals a new strategy for security identification of computers which can be potentially applied in cyber and information security.