Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and transmitting autonomous vehicle prepositioning instructions to improve network coverage. In particular, in one or more embodiments, the disclosed systems subdivide a geographic transportation service area into subregions, generate a set of waypoints and circuits for the subregions. Moreover, in one or more embodiments, the disclosed systems utilize an optimization model to assign autonomous vehicles to the set of waypoints and circuits and transmit digital prepositioning instructions to the autonomous vehicles to traverse the waypoints and circuits.

Abstract: Architectures and techniques for in-app behavior detection. A behavior detection agent within an application running on a hardware computing device captures events within the application. The events are inputs received from one or more sources external to the application. The behavior detection agent generates an event stream from the captured events. The behavior detection agent analyzes the event stream for significant feature frequencies and associations corresponding to one or more attack profiles. The behavior detection agent initiates an attack response in response to finding one or more significant feature frequencies and associations. The attack response comprises at least changing an operational configuration of the application.

Abstract: Among other things, embodiments of the present disclosure help identify anomalous web browser session behavior. Other embodiments may be described and/or claimed.

Abstract: Architectures and techniques for in-app behavior detection. A behavior detection agent within an application running on a hardware computing device captures events within the application. The events are inputs received from one or more sources external to the application. The behavior detection agent generates an event stream from the captured events. The behavior detection agent analyzes the event stream for significant feature frequencies and associations corresponding to one or more attack profiles. The behavior detection agent initiates an attack response in response to finding one or more significant feature frequencies and associations. The attack response comprises at least changing an operational configuration of the application.

Abstract: Architectures and techniques for in-app behavior detection. A behavior detection agent within an application running on a hardware computing device captures events within the application. The events are inputs received from one or more sources external to the application. The behavior detection agent generates an event stream from the captured events. The behavior detection agent analyzes the event stream for significant feature frequencies and associations corresponding to one or more attack profiles. The behavior detection agent initiates an attack response in response to finding one or more significant feature frequencies and associations. The attack response comprises at least changing an operational configuration of the application.

Abstract: Architectures and techniques for in-app behavior detection. A behavior detection agent within an application running on a hardware computing device captures events within the application. The events are inputs received from one or more sources external to the application. The behavior detection agent generates an event stream from the captured events. The behavior detection agent analyzes the event stream for significant feature frequencies and associations corresponding to one or more attack profiles. The behavior detection agent initiates an attack response in response to finding one or more significant feature frequencies and associations. The attack response comprises at least changing an operational configuration of the application.