Abstract: The present disclosure provides a system for improving security. The system may identify a query associated with a user account, and access an ID graph database to obtain an ID graph relating to the user account by a database driver. The system may also determine whether the user account is a target account type based at least on the ID graph. The ID graph may include a plurality of nodes and a plurality of edges. Each of the plurality of edges may connect two nodes. Each of the plurality of nodes may include at least one of a register ID, a login ID, a payment ID, a background check ID, or a face ID. Each edge that connects two nodes may include at least one of a user type associated with the two nodes, a timestamp when the edge is connected, or source information of the edge.

Abstract: Embodiments of the disclosure provide systems and methods for blocking a ride-hailing order. The method may include receiving incident data associated with a plurality of incidents. The incident data indicates a time and a location of each incident. The method may also include determining, by a processor, an area encompassing the locations of the plurality of incidents. The method may further include determining, by the processor, a plurality of time intervals each encompassing the time of at least one incident. The method may further include determining, by the processor, a time slot by merging the plurality of time intervals based on a time gap between every two neighboring time intervals. The method may further include designating, by the processor, a combination of the area and the time slot as a block zone and blocking an order generated from the area during the time slot of the block zone.

Abstract: Embodiments of the disclosure provide systems and methods for processing a transportation service request. An exemplary system may include a communication interface configured to receive the transportation service request from a terminal device. The system may further include at least one processor. The at least one processor may be configured to generate a passenger score based on the received transportation service request using a first machine learning model trained with sample passenger data associated with past impacted drivers. The at least one processor may further be configured to generate a trip score based on the generated passenger score and the received transportation service request using a second machine learning model trained with sample trip data associated with the past impacted drivers. The at least one processor may also be configured to allow or block the received transportation service request based on the generated trip score.