Abstract: Aspects of the subject disclosure may include, for example, obtaining a first group of Internet Protocol (IP) addresses from a group of network devices, and determining a second group of IP addresses from the first group of IP addresses includes possible malicious IP addresses utilizing a machine learning application. Further embodiments can include obtaining a first group of attributes of malicious IP addresses from a first repository, and determining a third group of IP addresses from the second group of IP addresses includes possible malicious IP addresses based on the first group of attributes. Additional embodiments can include receiving user-generated input indicating a fourth group of IP addresses from the third group of IP addresses includes possible malicious IP addresses, and transmitting a notification to a group of communication devices indicating that the fourth group of IP address includes possible malicious IP addresses. Other embodiments are disclosed.

Abstract: A method includes acquiring a plurality of hypertext transfer protocol (HTTP) session packets associated with activities of a plurality of known Trojans, wherein all of the Trojans are identified by a common signature identifier, extracting a plurality of request packets from the session packets, identifying a plurality of suspicious request packets within the plurality of request packets, grouping the plurality of suspicious request packets into a plurality of subsets, computing a centroid of one subset of the plurality of subsets, identifying a representative packet for the subset, wherein the representative packet is identified based on the centroid, and generating a signature for the one subset, based on the representative packet, wherein the signature is deployable by an intrusion detection system to detect an instance of a Trojan of the plurality of known Trojans.

Abstract: Controlling power factor correction (PFC) in a flyback converter is described. In one embodiment, an apparatus includes a flyback converter configured to operate with a variable switching frequency. The flyback converter includes a signal transformer, a primary side including a primary-side controller coupled to the signal transformer, and a secondary side including a secondary-side controller coupled to the signal transformer. The secondary-side controller is configured at least to cause a control signal to be generated based on a set of parameters. The control signal controls power factor correction (PFC) for the flyback converter.

Abstract: Controlling power factor correction (PFC) in a flyback converter is described. In one embodiment, an apparatus includes a flyback converter configured to operate with a fixed switching frequency. The flyback converter includes a signal transformer, a primary side including a primary-side controller coupled to the signal transformer, and a secondary side including a secondary-side controller coupled to the signal transformer. The secondary-side controller is configured at least to cause a control signal to be generated based on a ramp voltage generated by a ramp voltage generator of the secondary-side controller. The control signal provides power factor correction (PFC) using the flyback converter.

Abstract: A method includes acquiring a plurality of hypertext transfer protocol (HTTP) session packets associated with activities of a plurality of known Trojans, wherein all of the Trojans are identified by a common signature identifier, extracting a plurality of request packets from the session packets, identifying a plurality of suspicious request packets within the plurality of request packets, grouping the plurality of suspicious request packets into a plurality of subsets, computing a centroid of one subset of the plurality of subsets, identifying a representative packet for the subset, wherein the representative packet is identified based on the centroid, and generating a signature for the one subset, based on the representative packet, wherein the signature is deployable by an intrusion detection system to detect an instance of a Trojan of the plurality of known Trojans.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a first group of Internet Protocol (IP) addresses from a group of network devices, and determining a second group of IP addresses from the first group of IP addresses includes possible malicious IP addresses utilizing a machine learning application. Further embodiments can include obtaining a first group of attributes of malicious IP addresses from a first repository, and determining a third group of IP addresses from the second group of IP addresses includes possible malicious IP addresses based on the first group of attributes. Additional embodiments can include receiving user-generated input indicating a fourth group of IP addresses from the third group of IP addresses includes possible malicious IP addresses, and transmitting a notification to a group of communication devices indicating that the fourth group of IP address includes possible malicious IP addresses. Other embodiments are disclosed.

Abstract: A method includes acquiring a plurality of hypertext transfer protocol (HTTP) session packets associated with activities of a plurality of known Trojans, wherein all of the Trojans are identified by a common signature identifier, extracting a plurality of request packets from the session packets, identifying a plurality of suspicious request packets within the plurality of request packets, grouping the plurality of suspicious request packets into a plurality of subsets, computing a centroid of one subset of the plurality of subsets, identifying a representative packet for the subset, wherein the representative packet is identified based on the centroid, and generating a signature for the one subset, based on the representative packet, wherein the signature is deployable by an intrusion detection system to detect an instance of a Trojan of the plurality of known Trojans.

Abstract: Aspects of the subject disclosure may include, for example, facilitating a collaborative shopping session between first equipment of a first user and second equipment of a second user; obtaining a first shopping preference of the first user; obtaining a first image of first stock currently available for purchase in a first physical store; selecting, based at least in part upon the first shopping preference of the first user, a selected other physical store, the selected other physical store being selected from among at least a second physical store and a third physical store; obtaining a second image of second stock currently available for purchase in the selected other physical store; combining the first image and the second image into a combined image; sending to the first equipment the combined image; and sending to the second equipment the combined image. Other embodiments are disclosed.

Abstract: Creating and using learning models to identify botnet traffic can include obtaining netflow data associated with a connecting device that is communicating with a carrier network. The netflow data can represent communications associated with the connecting device. Data features associated with the communications can be extracted. The data features can include statistical information associated with the communications. A learning model based on the data features extracted from the netflow data can be trained. A prediction using the learning model can be generated, and an action based on the prediction can be taken.

Abstract: A system for providing realtime medical data to a client device regardless of a type of a client device's platform. The system uses different types of connections to establish a connection between the client device and the system and to transfer realtime medical data between the client device and the system. For example, a Hypertext Transfer Protocol (HTTP) connection can be used to establish a connection between the client device and the system and a websocket connection can be used to transfer realtime medical data between the client device and the system. By using an HTTP connection, the system can initially establish a connection between the system and any client device compatible with an HTTP connection.

Abstract: A system for providing realtime medical data to a client device regardless of a type of a client device's platform. The system uses different types of connections to establish a connection between the client device and the system and to transfer realtime medical data between the client device and the system. For example, a Hypertext Transfer Protocol (HTTP) connection can be used to establish a connection between the client device and the system and a websocket connection can be used to transfer realtime medical data between the client device and the system. By using an HTTP connection, the system can initially establish a connection between the system and any client device compatible with an HTTP connection.

Abstract: Disclosed are various embodiments for a resource allocation application. Usage data for application program interfaces is aggregated over time. Limits for an allocation of resources for each of the application program interfaces are calculated as a function of the usage data. Limits are recalculated as new application program interfaces are added.

Abstract: Disclosed are various embodiments for a resource allocation application. Usage data for application program interfaces is aggregated over time. Limits for an allocation of resources for each of the application program interfaces are calculated as a function of the usage data. Limits are recalculated as new application program interfaces are added.

Abstract: Disclosed are various embodiments for a resource allocation application. Usage data for application program interfaces is aggregated over time. Limits for an allocation of resources for each of the application program interfaces are calculated as a function of the usage data. Limits are recalculated as new application program interfaces are added.

Abstract: Embodiments are directed to a method, medium, and system for generating a distribution attribution value to analyze distribution of telecommunications services. The method including compiling values for at least three variable elements associated with the distribution of telecommunication services. A first total value being defined as a product of first element values associated with the at least three variable elements. A second total value being defined as a product of second element values associated with the at least three variable elements. The method also including generating an attribution value representing an amount of influence at least one of the at least three variable elements has on a difference between the first and the second total values. The attribution value being calculated using the first and second total values. Also, the attribution value being adapted to at least one of verify and adjust the distribution of telecommunication services.

Abstract: Embodiments are directed to a method, medium, and system for generating a distribution attribution value to analyze distribution of telecommunications services. The method including compiling values for at least three variable elements associated with the distribution of telecommunication services. A first total value being defined as a product of first element values associated with the at least three variable elements. A second total value being defined as a product of second element values associated with the at least three variable elements. The method also including generating an attribution value representing an amount of influence at least one of the at least three variable elements has on a difference between the first and the second total values. The attribution value being calculated using the first and second total values. Also, the attribution value being adapted to at least one of verify and adjust the distribution of telecommunication services.

Abstract: A method for monitoring the operation of a spacecraft make telemetry data directly accessible to customers of a satellite services provider over a network. The method may be completely automated at least from the perspective of the provider so that the need for human intervention during telemetry data retrieval and processing is eliminated. This, in turn, will substantially reduce the delays, costs, and inefficiencies associated with conventional telemetry data processing and customer service methods. In one application of the method, helix current data is automatically retrieved, processed, and made accessible at a service provider's website for retrieval by customers. The website may be password-protected for security purposes. If desired, telemetry data may be provided on the website on a real-time or near real-time basis. The method may advantageously be integrated into a customer service management model for a satellite service provider in order to streamline efficiency and reduce costs.