Abstract: Systems and methods for tracking, predicting, and mitigating Advanced Persistent Threat (APT) attacks in a network include obtaining data related to events and triggers for one or more attacks, wherein the data includes a plurality of i) virtual currency transactions, ii) network traffic flow, and iii) sentiment on any of social media, blogs, and news feeds; correlating the data with one or more subscribed entities; determining a threat index for an attack on a specific subscribed entity of the one or more subscribed entities through analysis of the correlated data, wherein the threat index provides a probability of the attack on the specific subscribed entity; and notifying the specific subscribed entity of a likelihood of the attack based on the threat index.

Abstract: A system for operating a network. The system includes a processor and memory storing instructions. The instructions, when executed by the processor, cause the processor to generate a network path from a source device to a destination device. The instructions include a path calculation engine (PCE) configured to select, from the network, a first intervening device for connecting the source device and the destination device to form the network path, further select, from the network and as additional candidates to form the network path, a first plurality of candidate devices to be in the network path with the first intervening device, and generate, according to a routing constraint of the network, the network path based on the first intervening device and a preference level of each of the first plurality of candidate devices.

Abstract: Systems and methods for tracking, predicting, and mitigating Advanced Persistent Threat (APT) attacks in a network include detecting, from monitoring, events related to one or more subscribed entities, wherein the monitoring includes two or more of analyzing traffic flow, analyzing virtual currency transactions, and monitoring information related to the one or more subscribed entities on the Internet; analyzing the events to determine a likelihood of an attack on a specific subscribed entity of the one or more subscribed entities; and causing mitigation of the attack based on the determined likelihood, wherein the mitigation comprises one or more actions in the network relative to the specific subscribed entity.

Abstract: A method, operated by a Software Defined Networking (SDN) controller associated with an Autonomous System (AS) with one or more peering points, each peering point with an associated router communicatively coupled to the SDN controller, the method for detecting and defending against Distributed Denial of Service (DDoS) attacks, and the method includes receiving data from the one or more peering points; detecting malicious traffic at the one or more peering points; determining a peer quality measurement for the one or more peering points; and communicating the peer quality measurement and other data associated with the malicious traffic to one or more other SDN controllers, associated with Autonomous Systems connected through the one or more peering points, to facilitate convergence of the peer quality measurement back to a nominal level.

Abstract: A system for operating a network. The system includes a processor and memory storing instructions. The instructions, when executed by the processor, cause the processor to generate a network path from a source device to a destination device. The instructions include a path calculation engine (PCE) configured to select, from the network, a first intervening device for connecting the source device and the destination device to form the network path, further select, from the network and as additional candidates to form the network path, a first plurality of candidate devices to be in the network path with the first intervening device, and generate, according to a routing constraint of the network, the network path based on the first intervening device and a preference level of each of the first plurality of candidate devices.

Abstract: A method and server to detect, diagnose, and mitigate issues in a network include receiving Operations, Administration, and Maintenance (OAM) data related to the network, the OAM data related to current operation of the network; instantiating a rule engine to evaluate one or more rules based on any one of the OAM data, an event, policy, and an anomaly; and performing one or more actions based on the evaluating the one or more rules. A Software Defined Networking (SDN) controller is also described.

Abstract: Systems and methods for tracking, predicting, and mitigating Advanced Persistent Threat (APT) attacks in a network include detecting, from monitoring, events related to one or more subscribed entities, wherein the monitoring includes two or more of analyzing traffic flow, analyzing virtual currency transactions, and monitoring information related to the one or more subscribed entities on the Internet; analyzing the events to determine a likelihood of an attack on a specific subscribed entity of the one or more subscribed entities; and causing mitigation of the attack based on the determined likelihood, wherein the mitigation comprises one or more actions in the network relative to the specific subscribed entity.

Abstract: A method and server to detect, diagnose, and mitigate issues in a network include receiving Operations, Administration, and Maintenance (OAM) data related to the network, the OAM data related to current operation of the network; instantiating a rule engine to evaluate one or more rules based on any one of the OAM data, an event, policy, and an anomaly; and performing one or more actions based on the evaluating the one or more rules. A Software Defined Networking (SDN) controller is also described.

Abstract: A method, operated by a Software Defined Networking (SDN) controller associated with an Autonomous System (AS) with one or more peering points, each peering point with an associated router communicatively coupled to the SDN controller, the method for detecting and defending against Distributed Denial of Service (DDoS) attacks, and the method includes receiving data from the one or more peering points; detecting malicious traffic at the one or more peering points; determining a peer quality measurement for the one or more peering points; and communicating the peer quality measurement and other data associated with the malicious traffic to one or more other SDN controllers, associated with Autonomous Systems connected through the one or more peering points, to facilitate convergence of the peer quality measurement back to a nominal level.