Abstract: Embodiments of the present disclosure relate systems and methods for detecting cognitive decline of a subject using passively obtained data from at least one mobile device. In an exemplary embodiment, a computer-implemented method comprises receiving passively obtained data from at least one mobile device. The method further comprises generating digital biomarker data from the passively obtained data. The method further comprises analyzing the digital biomarker data to determine whether the subject is exhibiting signs of cognitive decline.

Abstract: In an example embodiment, a Software Defined Networking (SDN) application identifies a domain based on a destination address of a packet that is associated with a primary service. The domain corresponds to the primary service, and the primary service is configured to trigger one or more support flows from one or more ancillary services. The SDN application identifies the one or more support flows based on the domain, and generates one or more rules for distribution to one or more network elements that handle packets of the one or more support flows from the one or more ancillary services.

Abstract: A method for applying a user-specific policy in a network. The method includes identifying a historical portion of network traffic of the network as associated with a user, analyzing, by a computer processor, the historical portion of network traffic to generate a fingerprint of the user, wherein the fingerprint represents characteristics of user activity in the network, identifying, by the computer processor, an ongoing portion of network traffic of the network as associated with the user, analyzing, by the computer processor and based on the fingerprint, the ongoing portion of network traffic to determine a match, wherein the match is determined at a time point within the ongoing portion of network traffic, and applying, in response to determining the match, the user-specific policy to the ongoing portion of network traffic subsequent to the time point.

Abstract: Presented herein are network traffic/flow monitoring techniques for identifying a primary/core domain that is representative of the service being accessed by a series/set of network flows, and grouping networking traffic flows that result from the user's accessing of the core domain. In one example, a plurality of core domains each corresponding to a primary web service configured to be directly accessed by network flows via one or more networks is identified. For each of the plurality of core domains, one or more models of traffic activity resulting from access to the corresponding primary web service by a network flow is generated. Based on the models of traffic activity, real-time network traffic flows are associated to a selected one of the core domains.

Abstract: In an example embodiment, a Software Defined Networking (SDN) application identifies a domain based on a destination address of a packet that is associated with a primary service. The domain corresponds to the primary service, and the primary service is configured to trigger one or more support flows from one or more ancillary services. The SDN application identifies the one or more support flows based on the domain, and generates one or more rules for distribution to one or more network elements that handle packets of the one or more support flows from the one or more ancillary services.

Abstract: Presented herein are network traffic/flow monitoring techniques for identifying a primary/core domain that is representative of the service being accessed by a series/set of network flows, and grouping networking traffic flows that result from the user's accessing of the core domain. In one example, a plurality of core domains each corresponding to a primary web service configured to be directly accessed by network flows via one or more networks is identified. For each of the plurality of core domains, one or more models of traffic activity resulting from access to the corresponding primary web service by a network flow is generated. Based on the models of traffic activity, real-time network traffic flows are associated to a selected one of the core domains.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, obtaining regression coefficients that quantify a relationship between premises feedback and first network and premises performance indicators, obtaining second network performance indicators for the network elements, obtaining second premises performance indicators for the customer premises equipment, and predicting customer complaints by applying the obtained regression coefficients to at least the second network performance indicators and the second premises performance indicators. Other embodiments are disclosed.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, obtaining regression coefficients that quantify a relationship between premises feedback and first network and premises performance indicators, obtaining second network performance indicators for the network elements, obtaining second premises performance indicators for the customer premises equipment, and predicting customer complaints by applying the obtained regression coefficients to at least the second network performance indicators and the second premises performance indicators. Other embodiments are disclosed.