A computer-implemented method for theft proofing an autonomous driving vehicle, ADV, the method comprising: receiving, by a theft detection module from a plurality of sensors, which are, one or more cameras, weighting machine and movement sensor of the ADV sensor system, sensor data of a moving object representing a person within a predetermined proximity of the ADV for transporting goods, wherein the sensor data includes a plurality of images of the moving object, and real-time weights and movements of the ADV; determining a moving behavior of the moving object based on the sensor data in view of a set of known moving behaviors; determining whether an intention of the person is likely to remove at least some of the goods from the ADV based on the moving behavior and other indicators, wherein a set of features is extracted from the images of the moving object and are fed into a theft predictive 2. model to determine whether such a behavior is associated with a predetermined theft behavior, and the theft predictive model is trained using a set of known theft behaviors in the past, the other indicators comprising an erratic movement of the ADV indicating that the ADV is likely to be taken away are used for determining a likely theft intention of the person, wherein the erratic movement of the ADV is determined based on real time movements of the ADV generated by the movement sensor installed in the ADV, wherein other indicators and the moving behavior are used for determining the likely theft intention of the person; and sending an alarm to a predetermined destination in response to determining that the intention of the person is likely to remove the at least a portion of the goods from the ADV. receiving, by a theft detection module from a plurality of sensors, which are, one or more cameras, weighting machine and movement sensor of the ADV sensor system, sensor data of a moving object representing a person within a predetermined proximity of the ADV for transporting goods, wherein the sensor data includes a plurality of images of the moving object, and real-time weights and movements of the ADV; determining a moving behavior of the moving object based on the sensor data in view of a set of known moving behaviors; determining whether an intention of the person is likely to remove at least some of the goods from the ADV based on the moving behavior and other indicators, wherein a set of features is extracted from the images of the moving object and are fed into a theft predictive 2. model to determine whether such a behavior is associated with a predetermined theft behavior, and the theft predictive model is trained using a set of known theft behaviors in the past, the other indicators comprising an erratic movement of the ADV indicating that the ADV is likely to be taken away are used for determining a likely theft intention of the person, wherein the erratic movement of the ADV is determined based on real time movements of the ADV generated by the movement sensor installed in the ADV, wherein other indicators and the moving behavior are used for determining the likely theft intention of the person; and sending an alarm to a predetermined destination in response to determining that the intention of the person is likely to remove the at least a portion of the goods from the ADV.