Abstract: Systems and methods for predicting user lifetime value in accordance with embodiments of the invention are disclosed. In one embodiment, a lifetime value prediction server system includes a processor, and a memory configured to store a lifetime value prediction application, wherein the lifetime value prediction application directs the processor to obtain a set of user interaction data, group the set of user interaction data into cohorts, where the user interaction data within a cohort occurs on a particular day, calculate a set of known spending values based on the cohorts, determine a set of predicted spending values based on the set of known spending values, determine a set of predicted spending confidence values based on the set of known spending values, and calculate a set of predicted lifetime value data based on the set of predicted spending values and the set of predicted spending confidence values.

Abstract: A system and method are provided for detecting malicious or unwanted software, or malicious or unauthorized access to cyber-physical system devices. The activity and applications on the device are analyzed by various methods including machine learning algorithms and the results are reported. Malicious or unwanted 5 activity or applications can be stopped by the device user or other authorized person.

Abstract: Systems and methods for predicting user lifetime value in accordance with embodiments of the invention are disclosed. In one embodiment, a lifetime value prediction server system includes a processor, and a memory configured to store a lifetime value prediction application, wherein the lifetime value prediction application directs the processor to obtain a set of user interaction data, group the set of user interaction data into cohorts, where the user interaction data within a cohort occurs on a particular day, calculate a set of known spending values based on the cohorts, determine a set of predicted spending values based on the set of known spending values, determine a set of predicted spending confidence values based on the set of known spending values, and calculate a set of predicted lifetime value data based on the set of predicted spending values and the set of predicted spending confidence values.

Abstract: A deep packet inspection (DPI) allocator for managing bandwidth in a communication channel, the DPI allocator comprising: a DPI application for inspecting data packets propagating to a destination via the channel that enter the allocator; and at least one service application for processing data packets that enter the allocator.

Abstract: A deep packet inspection (DPI) allocator for managing bandwidth in a communication channel, the DPI allocator comprising: a DPI application for inspecting data packets propagating to a destination via the channel that enter the allocator; and at least one service application for processing data packets that enter the allocator.

Abstract: A deep packet inspection (DPI) allocator for managing bandwidth in a communication channel, the DPI allocator comprising: a DPI application for inspecting data packets propagating to a destination via the channel that enter the allocator; and at least one service application for processing data packets that enter the allocator.

Abstract: A deep packet inspection (DPI) allocator for managing bandwidth in a communication channel, the DPI allocator comprising: a DPI application for inspecting data packets propagating to a destination via the channel that enter the allocator; and at least one service application for processing data packets that enter the allocator.