Tactile sensors are increasingly important in advancing future robotic technologies, human-machine interfaces, health monitoring devices, and artificial receptors. However, the output signals of layered capacitive tactile sensors are often susceptible to interference from adjacent touch-induced movements caused by electrostatic effects. In contrast, tactile sensors based on triboelectric nanogenerators (TENG) offer enhanced sensitivity to pressure stimuli and object recognition capabilities. Here, we developed a bimodal capacitive tactile sensor that incorporates TENG layers, resulting in a sensor design that closely mimics the mechanical receptors found in humans. The bimodal tactile sensors consist of seven stacked layers, exhibiting reliable tactile sensing abilities while being shielded by the top TENG layers. Nevertheless, The TENG layers acts as a pioneer during the touching to recognize the adjacent objects. Furthermore, we illustrate the capabilities of such sensors by utilizing them in a self-developed two-tier authentication system accepting designative pressure pattern and prescriptive individual as passwords. Such form of application no only suggests immense potential of this sensor but also proves the huge function of bimodal sensor for internet of things (IoT) interaction with human.