Biometric signatures based on either the physiological or behavioural features of a person have been widely used for identification and authentication. However, few strategies have been developed that combine the two types of features in one signature. Here, we report a type of biometric signature based on the triboelectricity of the human body (TEHB) that combines these two types of features. This triboelectric biometric signature (TEBS) can be accomplished by anyone regardless of the physical condition, as it can be performed by many parts of the body. Different TEBS can be identified using a convolutional neural network (CNN) model with a test accuracy of up to 1.0. The TEBS has been further used for text encryption and decryption with a high sensitivity to changes. Moreover, a dual signed digital signature for enhanced security has been proposed. Our findings provide a new type of TEBS that can be generally used and demonstrated in applications.