Methods, systems, and devices for dynamically modeling and grouping endpoints for edge networking
Various embodiments described herein disclose an endpoint modeling and grouping management system that can collect data from endpoint computer devices in a network. In some embodiments, agents installed on the endpoints can collect real-time information at the kernel level providing the system with deep visibility. In some embodiments, the endpoint modeling and grouping management system can identify similarities in behavior in response to assessing the data collected by the agents. In some embodiments, the endpoint modeling and grouping management system can dynamically model groups such as logical groups, and cluster endpoints based on the similarities and/or differences in behavior of the endpoints. In some embodiments, the endpoint modeling and grouping management system transmits the behavioral models to the agents to allow the agents to identify anomalies and/or security threats autonomously.
1. A dynamic endpoint-based edge networking system for protecting security and integrity of an elastic computer network, the system comprising:
a plurality of agents, wherein each agent of the plurality of agents is installed on a target endpoint device, the target endpoint device being one of a plurality of endpoint devices forming an elastic computer network, and wherein, for each agent of the plurality of agents, the agent is configured to:
access an operating system of the target endpoint device on which the agent is installed to obtain visibility of operating system processes and network communications of the target endpoint device;
monitor the operating system processes and the network communications of the target endpoint device to obtain target endpoint data, the target endpoint data comprising information regarding at least one of the system processes or network processes of the target endpoint device;
transmit the target endpoint data to a central server system;
identify, using a local security protocol, one or more local anomalous indicators on the target endpoint device based at least in part on the target endpoint data; and
respond to the one or more local anomalous indicators on an endpoint-level based at least in part on the local security protocol,
wherein the local security protocol comprises one or more rule sets, policies, or access rights designed to ensure local security of each of the plurality of endpoint devices; and
a central server system comprising:
one or more computer readable storage devices configured to store a plurality of computer executable instructions; and
one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the central server system to:
receive the target endpoint data from each of the plurality of agents installed on a target endpoint device;
analyze the target endpoint data received from each of the plurality of agents to identify network-wide activity patterns;
identify, using a network-wide security protocol, one or more network-wide anomalous indicators on a network level across the plurality of endpoint devices based at least in part on the identified network-wide activity patterns; and
respond to the one or more network-wide anomalous indicators on the network level across the plurality of endpoint devices based at least in part on the network-wide security protocol.
2. The dynamic endpoint-based edge networking system of claim 1 , wherein monitoring the operating system processes and the network communications of the target endpoint device comprises continuously verifying and authenticating target endpoint activities.
3. The dynamic endpoint-based edge networking system of claim 1 , wherein the plurality of endpoint devices comprise one or more cellphones, servers, virtual machines, laptops, tablets, desktop computers, Internet of Things (IoT) devices, landline phones, wearable devices, or smart home devices.
4. The dynamic endpoint-based edge networking system of claim 1 , wherein the local anomalous indicator comprises activities of malicious software on the target endpoint device.
5. The dynamic endpoint-based edge networking system of claim 4 , wherein the malicious software comprises a virus, malware, ransomware, adware, spyware, Trojan horse, worm, rootkit, scareware, rogueware, active content software, or logic bomb.
6. The dynamic endpoint-based edge networking system of claim 4 , wherein the malicious software comprises zero-day software.
7. The dynamic endpoint-based edge networking system of claim 1 , wherein responding to the one or more local anomalous indicators based on the local security protocol comprises controlling one or more operating system processes or network communications of the target device.
8. The dynamic endpoint-based edge networking system of claim 1 , wherein responding to the one or more local anomalous indicators based on the local security protocol comprises limiting one or more operating system processes or network communications of the target device.
9. The dynamic endpoint-based edge networking system of claim 8 , wherein limiting one or more operating system processes or the network communications of the target device effectively isolates malicious software located on the target endpoint.
10. The dynamic endpoint-based edge networking system of claim 1 , wherein at least one endpoint device of the plurality of endpoint devices is located outside of a computer network firewall.
11. The dynamic endpoint-based edge networking system of claim 1 , wherein one or more of the central server system or plurality of agents is further configured to analyze the target endpoint data to determine typical network access behavior and typical processor behavior of the target endpoint.
12. The dynamic endpoint-based edge networking system of claim 11 , wherein the determined typical network access behavior and typical processor behavior of the target endpoint is used to update the local security protocol.
13. The dynamic endpoint-based edge networking system of claim 11 , wherein one or more artificial intelligence (AI) techniques are employed by one or more of the central server system or plurality of agents to analyze the target endpoint data to determine typical network access behavior and typical processor behavior of the target endpoint.
14. The dynamic endpoint-based edge networking system of claim 1 , wherein the central server system is further caused to group and one or more endpoints of the plurality of endpoints into an endpoint cluster, wherein the one or more endpoints of the endpoint cluster comprise one or more similar processing or network access patterns.
15. The dynamic endpoint-based edge networking system of claim 14 , wherein the central server system is further caused to generate and assign a common local security protocol to each of the one or more endpoints of the endpoint cluster.
16. The dynamic endpoint-based edge networking system of claim 1 , wherein each of the plurality of agents is further configured to perform a point-in-time validation of the target endpoint device, wherein the point-in-time validation comprises a verification that no local anomalous indicators are present on the target endpoint device.
17. The dynamic endpoint-based edge networking system of claim 1 , wherein the local anomalous indicator is a pattern of local anomalous activity on the target endpoint device.
18. The dynamic endpoint-based edge networking system of claim 1 , wherein one or more of the local security protocol or the network-wide security protocol is manually configured by a network administrator.
19. The dynamic endpoint-based edge networking system of claim 1 , wherein one or more of the local security protocol or the network-wide security protocol is based on a pre-configured rule set.
20. The dynamic endpoint-based edge networking system of claim 1 , wherein one or more of the local security protocol or the network-wide security protocol is automatically generated and assigned by one or more of the central server system or plurality of agents.