Abstract: An object of the present invention is to provide a personal information protection apparatus, a personal information protection method, and a program that make it possible to easily control a range of personal information to be provided to an application. The personal information protection apparatus according to the present invention performs machine learning on terms of use, classifications, and access settings of applications installed in a terminal, and holds them as a user policy, and when an attempt is made to change the access settings of a certain application, presents, to the user, recommended settings based on the user policy. When the user changes access settings of an application based on a policy that is different from the prior and existing policy, this personal information protection apparatus performs learning on the user policy again using the changed access settings.

Abstract: The route control method and the route setting device according to the present invention is configured such that a learning unit is prepared for each path, a function form of the learning unit of the path in forwarding a packet is adjusted by having traffic information (packet arrival rate, queue length, and the like) and congestion information (congested or not congested) of this path as teacher data, and when this path is congested, changing to a path with an output of no congestion among the learning units is executed. Thus, since the learning unit optimizes the function form, changing to an alternative path can be immediately executed even when the congestion incidentally occurs on the path.

Abstract: The route control method and the route setting device according to the present invention is configured such that a learning unit is prepared for each path, a function form of the learning unit of the path in forwarding a packet is adjusted by having traffic information (packet arrival rate, queue length, and the like) and congestion information (congested or not congested) of this path as teacher data, and when this path is congested, changing to a path with an output of no congestion among the learning units is executed. Thus, since the learning unit optimizes the function form, changing to an alternative path can be immediately executed even when the congestion incidentally occurs on the path.