Beijing Didi Infinity Technology and Development Co., Ltd.

Didi Research America, LLC

Jing Chen

Dong Li

Huaiyu Zhu

Deyu Hu

Zihan Yi

Michael Lin

Junbo Shi

Shray Kapoor

Haocheng Zhang

Yichong Lin

Liwei Ren

Xin Chen

Conghui Fu

Kang Yuan

Incidents may be monitored using a camera in response to an activation of a trigger device. Trigger data may be received over a communication network in response to activation of a trigger device disposed within a first area of a vehicle. A camera disposed within a second area of the vehicle may be controlled over the communication network in response to receiving the trigger data, the controlling causing the camera to capture sensor information of a passenger of the vehicle. Passenger information of the passenger of the vehicle may be obtained in response to receiving the trigger data. An alert notification may be generated. The alert notification may comprise at least a portion of the sensor information of the passenger, and the alert notification may be capable of initiating one or more incident actions associated with the passenger.

Cloud-controlled vehicle security system

After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Augmented passenger verification

Dynamic geofence zones may be deployed and updated for a ride sharing service. At least one set of dynamic geofence zones may be created which are associated with a ride sharing service. At least one time period may be set for the at least one set of dynamic geofence zones. The at least one set of dynamic geofence zones may be deployed. The at least one set of dynamic geofence zones may be updated.

Dynamic geofence zones for ride sharing

After receiving a trip request, a ridesharing platform system can determine scores for each prior trip request within a time window from features associated with the prior trip request. The ridesharing platform system can determine patterns from corresponding scores and determine a risk for the trip request using on the patterns. The ridesharing platform system can determine whether to accept or decline the trip request based on the risk for the trip request.

Identifying high risk trips using continuous call sequence analysis

Systems and methods are provided for data security grading. An exemplary method for data security grading, implementable by a computer, may comprise receiving a request to access a query data field, searching for the query data field from a security level table, in response to finding the query data field from the security level table, obtaining from the security level table a security level corresponding to the query data field, and in response to not finding the query data field from the security level table, determining a security level corresponding to the query data field based at least on a lineage tree and the security level table. The lineage tree may trace the query data field to one or more source data fields, and the security data level table may comprise one or more security levels corresponding to the one or more source data fields.

System and method for data security grading

A route may be recommended, and it may be determined if a vehicle detours from the recommended route. At least one recommend route may be obtained. A current route of a vehicle may be obtained. A variance value may be determined based on the current route and the at least one recommend route. The variance value may be compared to a threshold. It may be determined whether the variance value exceeds the threshold. If the variance value exceeds the threshold, it may be determined that the vehicle has detoured. If the variance value does not exceed the threshold, it may be determined that the vehicle has not detoured.

Vehicle detour monitoring

Systems and methods are provided for near real-time IP user mapping. Such methods may include obtaining IP address assignment data points from different sources including an authentication, authorization, and accounting (AAA) server of a private network, a service provider that provides a computer-based service within the private network, and user devices that have access to the private network. The methods may also include applying an IP mapping rule to the obtained IP address assignment data points to generate IP address mapping.

Method and system for near real-time IP user mapping

Mismatched drivers may be identified based on passenger evaluations. A set of evaluations may be obtained. Each evaluation in the set of evaluations may be based on whether a current driver matches a registered driver. A convergence point number may be obtained. The convergence point number may be a number of evaluations required for accurate identification. An identification rate may be computed based on the set of evaluations and the convergence point number. The current driver may be verified based on a comparison of the identification rate to a threshold match rate. If the identification rate is greater than a threshold match rate, it may be determined that the identity of the current driver is valid. If the identification rate is not greater than a threshold match rate, the current driver may be identified as a mismatched driver.

Mismatched driver detection

Methods, apparatuses, and storage media storing instructions for scanning electronically-stored files are provided. A file stored in a computer-readable storage medium is scanned. Based on the scanning, a common analysis is performed on the file for two or more software functions. Based on the scanning, a software function-specific analysis is performed on the file for a respective software function. Two or more decisions on the file is made for the two or more software functions based on the common analysis and the software function-specific analysis.

Multi-purpose agent for endpoint scanning

Safety geofence zones may be created and deployed for a ride sharing service. At least one set of safety geofence zones may be created which are associated with a ride sharing service. A zone type may be set for each set of safety geofence zones in the at least one set of safety geofence zones. At least one trigger condition may be set for the at least one set of safety geofence zones. The at least one set of safety geofence zones may be deployed.

Safety geofence zone deployment

Incidents may be detected and reported based on changes in sensor data from a device. Trigger data from a trigger device in a vehicle may be received over a communication network. An incident report may be generated based on the trigger data. The incident report may comprise driver information of a driver of the vehicle. A user account of the driver in a ride sharing application may be blocked.

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Palo Alto, CA, United States of America

Jing Chen