Ciena Corporation

Cienna Corporation

Roger Michael Elbaz

Aung Htay

Sachin Subhedar

David Côté

Logan Blyth

William Webb

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.

Systems and methods for tracking, predicting, and mitigating advanced persistent threats in networks

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.

Systems and methods for Software Defined Networking (SDN) orchestration of antennas and frequencies in a heterogeneous Radio Access Network (RAN) include maintaining status of a plurality of devices connected to the heterogeneous RAN; determining whether to upgrade connections of a first subset of the plurality of devices; determining whether to downgrade connections of a second subset of the plurality of devices; and providing instructions to the heterogeneous RAN for the first subset and the second subset. The systems and methods enable enforcement of business-aware prioritization on the heterogeneous RAN.

SDN orchestration and optimization of antennas and frequencies in radio access networks

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.

Systems and methods utilizing peer measurements to detect and defend against distributed denial of service attacks

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.

Systems and methods to detect, diagnose, and mitigate issues in multi-layer networks

Systems and methods to detect and characterize fake cell towers in a network operator's network include receiving live data comprising any of crowd-sourced data and tower data; performing live data analysis on the live data and reference data; and detecting the fake cell towers based on the live data analysis. Optionally, spectrum data captured at cell towers by a baseband processor coupled to backhaul equipment can be used as additional input.

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Alpharetta, GA, United States of America

Roger Michael Elbaz