Level 3 Communications, LLC

Michael Benjamin

Skyler Jameson Bingham

John Sherwood Reynolds, Ii

Peter Brecl

Mark Dehus

David Dubois

Christopher Smith

Jamie Lin

John Knies

Sylvan H Morley, Iii

Aspects of the present disclosure involve utilizing network threat information to manage one or more security devices or policies of a communication network. The security system may receive threat intelligence data or information associated with potential threats to a communications network and process the threat intelligence data to determine one or more configurations to apply to security devices of a network. The system may then generate a rule or action to respond to the identified attack, such as a firewall rule for a firewall device to block traffic from the source of the attack. The threat intelligence information may include a confidence score indicating a calculated confidence in the identification of the malicious communications, which may be utilized by the system to determine the type of action taken on the security devices of the network in response to the information or data.

System and method for utilization of threat data for network security

Systems and methods for managing network devices include performing clustering operations for network devices based on attributes of the network devices. By comparing the results of subsequent clustering operations, changes in network device attributes can be readily identified and any network devices for which attributes have changed may be subject to further investigation or remedial action (e.g., blocking traffic to/from the network device). Clustering may also be used to conduct an inventory of network devices by identifying groups of network devices that have similar attributes.

Systems and methods for network device management using device clustering

Examples of the present disclosure describe systems and methods for providing enhanced security in edge computing environments. A first aspect describes a method for moving security features dynamically applied to an application at a first deployment location to an application at a second deployment location. A second aspect describes a method for locally expanding/contracting an instance of a deployed application. A third aspect describes a method for redirected network traffic associated with detected malicious conduct from a first application deployment environment to a secured second application deployment environment. A fourth aspect describes a method for performing multi-stage network traffic filtering.

Systems and methods for providing enhanced security in edge computing environments

Authorization for a user may be dynamically tailored per application or per application function, rather than globally managed by an administrator. For example, in some embodiments, an identity access management system may generate a suitable authorization token (or authorization token information) to enable a user to login to an application or perform a particular function. The authorization token may be dynamically generated and tailored based on filtering various identity information otherwise available from an identity system, access boundaries of applicable application functions, or other factors.

Identity access management system and method

A route viewing system includes a computing system that receives information associated with one or more routes through a network, and identifies the routes that are associated with at least one illicit user computer used by an illicit user. The computing system then obtains a source location of a source address of the routes and a destination location of a destination address of the routes, and displays the routes on a geographical display at the source location of the source address and the destination location of the destination address of each of the routes.

Illicit route viewing system and method of operation

The present application describes a system that uses endpoint data and network data to detect an anomaly. Once an anomaly is detected, the system may determine a severity of the anomaly by comparing the anomaly to a global database of known anomalies. The system may then initiate preventative measures to address the anomaly.

Collecting endpoint data and network data to detect an anomaly

Systems and methods for implementing filters within computer networks include obtaining blocklist data that includes blocklist entries for a network. Each of the blocklist entries includes one or more network traffic attributes for identifying traffic to be blocked. In response to receiving the blocklist data, a filter based on a common network traffic attribute shared between at least two of the plurality of blocklist entries is generated. The filter is then deployed to a network device within the network such that the filter may be implemented at the network device to block corresponding traffic.

Dynamic filter generation and distribution within computer networks

Aspects of the present disclosure involve systems and methods for utilizing verified autonomous system (AS) network interconnections received via a cryptographically certified Recognized Operating Agency (ROA) object to generate an interconnect network model which may be used as a reference model to mitigate hijacking of network communications in downstream route announcements. In particular, AS networks may announce or share a cryptographically certified ROA object that includes a list of other AS networks to which the announcing network is connected. A router, server, or other networking device may receive ROA objects from multiple AS networks and generate a model or graph of the interconnectedness of the AS networks. Further, because each ROA object may be cryptographically certified or signed, the networking device may trust the information provided in the received ROA objects. The networking device may further verify announced routing information against the generated network model.

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Broomfield, CO, United States of America

Michael Benjamin