Mobile management system

1. A mobile management method comprising:

receiving from an application on a client a DNS query for a host name;

retrieving reputation data associated with the host name from a local cache on the client;

determining a policy for the host name, which is associated with the host name and the reputation data associated with the host name; and

determining, based on the determined policy for the host name, an action for network flows to be taken,

wherein the determined action for the network flows is selected from the group comprising:

sending the network flows through a VPN tunnel to a server,

sending the network flows out of a local proxy on the client to a private or public network, and

blocking the network flows;

sending at least network flow metadata to a collector on the client; and

transmitting the network flow metadata in the collector to a VPN server pool via the VPN tunnel,

wherein, whether the network flows are sent through the VPN tunnel, sent out of the local proxy or blocked, the network flow metadata is sent to the VPN server pool, and

wherein the VPN server pool comprises a data gateway that receives the network flow metadata, and

a data publisher coupled to the data gateway instructs at least one of:

a reporting engine to generate at least one of reports or dashboards; or

a machine learning unit to find anomalies, determine cohorts, deduce trends, determine location boundaries, detect network security issues, detect compromised devices, and/or optimize network usage.

2. The mobile management method according to claim 1 , wherein, based upon the found anomalies, determined cohorts, deduced trends, determined location boundaries, detected network security issues, detect compromised devices, and optimized network usage, the machine learning unit sends an alert to the VPN server pool; and

the VPN server pool one of sends an alert to the client or sends an update to the client.

3. The mobile management method according to claim 1 , wherein the machine learning unit comprises a data storage server collecting and storing network flow metadata from the VPN server pool and an analysis server, and the method further comprises:

aggregating in the analysis server the collected network flow metadata stored on the data storage server using statistical algorithms; and

processing the aggregated metadata through machine learning algorithms to automatically detect at least one of abnormal data transfers or usage that is abnormal for a user of the client.

4. The mobile management method according to claim 1 , further comprising updating the reputation data for the host name each time a DNS query for the host name is received by the client.

5. The mobile management method according to claim 4 , wherein the updating of the reputation data for the host name comprises:

sending a request through the VPN tunnel to retrieve reputation data for the host name from the server; and

receiving the retrieved reputation data for the host name from the server through the VPN tunnel.

6. The mobile management method according to claim 1 , wherein, when the DNS query for the host name is resolved in the client, the method further comprises:

returning the resolved host name to the application;

receiving a request for forwarding the network flows to a remote host for the resolved host name;

retrieving reputation data associated with the remote host from the local cache on the client;

determining whether a policy associated with the remote host and the reputation data associated with the remote host exists; and

one of:

sending the network flows one of: through a VPN tunnel to a server or out of a local proxy on the client to a private or public network; or

blocking the network flows

based on the determined policy for the remote host.

7. A mobile management method comprising:

receiving from an application on a client a DNS query for a host name;

retrieving reputation data associated with the host name from a local cache on the client;

determining a policy for the host name, which is associated with the host name and the reputation data associated with the host name;

determining, based on the determined policy for the host name, an action for network flows to be taken,

wherein the determined action for the network flows is selected from the group comprising:

sending the network flows through a VPN tunnel to a server,

sending the network flows out of a local proxy on the client to a private or public network, and

blocking the network flows;

sending at least network flow metadata to a collector on the client; and

transmitting the network flow metadata in the collector to a VPN server pool via the VPN tunnel,

wherein the VPN server pool comprises a machine learning unit using artificial intelligence and machine learning to determine boundaries of normal locations of at least one of individual client devices or device cohorts and to detect when an individual device or device cohort is outside of the normal locations.

8. A mobile management method comprising:

receiving from an application on a client a DNS query for a host name;

retrieving reputation data associated with the host name from a local cache on the client;

determining a policy for the host name, which is associated with the host name and the reputation data associated with the host name; and

determining, based on the determined policy for the host name, an action for network flows to be taken,

wherein the determined action for the network flows is selected from the group comprising:

sending the network flows through a VPN tunnel to a server,

sending the network flows out of a local proxy on the client to a private or public network, and

blocking the network flows;

sending at least network flow metadata to a collector on the client; and

transmitting the network flow metadata in the collector to a VPN server pool via the VPN tunnel,

wherein the VPN server pool comprises a machine learning unit using artificial intelligence and machine learning to make findings and detections based upon at least the network flow metadata, and based on the findings and detections of the artificial intelligence and machine learning, the method further comprises at least one of:

allowing or blocking traffic;

switching between using different network interfaces;

using multiple network interfaces;

using or not using a proxy server;

switching between different proxy servers;

forcing compression between two devices;

forming forward error detection between two devices;

causing a device to launch an application;

causing a device to run diagnostics;

forcing advanced authentication;

enabling advanced logging;

throttling network usage;

limiting network destinations;

quarantining the device client; or

forcing traffic through encrypted tunnels.

9. A mobile management method comprising:

receiving from an application on a client a DNS query for a host name;

retrieving reputation data associated with the host name from a local cache on the client;

determining a policy for the host name, which is associated with the host name and the reputation data associated with the host name; and

determining, based on the determined policy for the host name, an action for network flows to be taken,

wherein the determined action for the network flows is selected from the group comprising:

sending the network flows through a VPN tunnel to a server,

sending the network flows out of a local proxy on the client to a private or public network, and

blocking the network flows, and

wherein, when the DNS query for the host name cannot be resolved in the client, the method further comprises:

sending the DNS query to a VPN server pool through the VPN tunnel;

receiving a resolved host name through the VPN tunnel and forwarding the resolved host name to the application;

receiving a request for forwarding the network flows to a remote host for the resolved host name;

retrieving reputation data associated with the remote host from the local cache on the client;

determining whether a policy associated with the remote host and the reputation data associated with the remote host exists; and

one of:

sending the network flows one of: through a VPN tunnel to a server or out of a local proxy on the client to a private or public network; or

blocking the network flows

based on the determined policy for the remote host.

10. The mobile management method according to claim 9 , wherein the client is a mobile client roaming between plural dissimilar networks, and wherein the DNS query is processed while the VPN tunnel is established over a first network and the network flows, to the remote host, are sent through the VPN tunnel while it is established over a second network dissimilar to the first network.

11. A mobile management method comprising:

receiving from an application on a client a DNS query for a host name;

retrieving reputation data associated with the host name from a local cache on the client;

determining a policy for the host name, which is associated with the host name and the reputation data associated with the host name; and

determining, based on the determined policy for the host name, an action for network flows to be taken,

wherein the determined action for the network flows is selected from the group comprising:

sending the network flows through a VPN tunnel to a server,

sending the network flows out of a local proxy on the client to a private or public network, and

blocking the network flows, and

wherein, when the DNS query for the host name cannot be resolved in the client, the method further comprises:

sending the DNS query to a local network;

receiving a resolved host name through the local network and forwarding the resolved host name to the application;

receiving a request for forwarding the network flows to a remote host for the resolved host name;

retrieving reputation data associated with the remote host from a local cache on the client;

determining whether a policy associated with the remote host and the reputation data associated with the remote host exists; and

one of:

sending the network flows one of: through a VPN tunnel to a server or out of a local proxy on the client to a private or public network; or

blocking the network flows

based on the determined policy for the remote host.

12. A mobile management method comprising:

sending at least network flow metadata to a collector on a client;

transmitting the network flow metadata in the collector to a VPN server pool via a VPN tunnel;

processing the network flow metadata to find and detect events and conditions within a network;

sending the found and detected events and conditions to the client;

determining whether a policy associated with the found and detected events and conditions exists; and

changing at least one of network usage or device behaviors based on the determined policy,

wherein, whether network flows are sent through the VPN tunnel, sent out of a local proxy or blocked, the network flow metadata is sent to a data gateway on a server, and

wherein a data publisher coupled to the data gateway instructs at least one of:

a reporting engine to generate at least one of reports or dashboards; or

a machine learning unit to find anomalies, determine cohorts, deduce trends, determine location boundaries, detect network security issues, detect compromised devices, and/or optimize network usage.

13. The mobile management method according to claim 12 , wherein, based upon the found anomalies, determined cohorts, deduced trends, determined location boundaries, detected network security issues, detected compromised devices, and optimize optimized network usage, the machine learning unit sends an alert to the VPN server pool; and

the VPN server pool one of sends an alert to the client or sends an update to the client.

14. The mobile management method according to claim 12 , wherein the machine learning unit comprises a data storage server collecting and storing network flow metadata from the VPN server pool and an analysis server, and the method further comprises:

aggregating in the analysis server the collected network flow metadata stored on the data storage server using statistical algorithms; and

processing the aggregated metadata through machine learning algorithms to automatically detect at least one of abnormal data transfers or usage that is abnormal for a user of the client.

15. The mobile management method according to claim 14 , wherein the processing of the aggregated metadata through the machine learning algorithms comprises at least one of:

processing the aggregated metadata through a variational autoencoder machine learning algorithm to automatically find and detect the events and the conditions without human aid;

processing the aggregated metadata through an overcomplete autoencoder machine learning algorithm to automatically find and detect the events and the conditions without human aid; or

processing the aggregated metadata through an undercomplete autoencoder machine learning algorithm to automatically find and detect the events and the conditions without human aid.

16. A mobile management method comprising:

sending at least network flow metadata to a collector on a client;

transmitting the network flow metadata in the collector to a VPN server pool via a VPN tunnel;

processing the network flow metadata to find and detect events and conditions within a network;

sending the found and detected events and conditions to the client;

determining whether a policy associated with the found and detected events and conditions exists; and

changing at least one of network usage or device behaviors based on the determined policy, and

wherein the VPN server pool comprises a machine learning unit using artificial intelligence and machine learning to determine boundaries of normal locations of at least one of individual client devices or device cohorts and to detect when an individual device or device cohort is outside of the normal locations.

17. A mobile management method comprising:

sending at least network flow metadata to a collector on a client;

transmitting the network flow metadata in the collector to a VPN server pool via a VPN tunnel;

processing the network flow metadata to find and detect events and conditions within a network;

sending the found and detected events and conditions to the client;

determining whether a policy associated with the found and detected events and conditions exists; and

changing at least one of network usage or device behaviors based on the determined policy, and wherein the VPN server pool comprises a machine learning unit using artificial intelligence and machine learning to find and detect the events and the conditions based upon at least the network flow metadata, and based on the events and conditions found and detected by the artificial intelligence and machine learning, the method further comprises at least one of:

allowing or blocking traffic;

switching between using different network interfaces;

using multiple network interfaces;

using or not using a proxy server;

switching between different proxy servers;

forcing compression between two devices;

forming forward error detection between two devices;

causing a device to launch an application;

causing a device to run diagnostics;

forcing advanced authentication;

enabling advanced logging;

throttling network usage;

limiting network destinations;

quarantining the client; or

forcing traffic through encrypted tunnels.