Analyzing and recommending rogue classification policies for a communication network

A computer system, comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable storage media storing programming for execution by the one or more processors, the programming comprising instructions to:
• obtain, at a plurality of times, rogue classification information for electronic devices detected within a communication network, the rogue classification information for each time of the plurality of times comprising:
• timestamp information identifying the time of the plurality of times;
• corresponding sets of attribute values for the electronic devices detected within the communication network at the time;
• and
• respective rogue classifications, as determined according to active rogue classification policies and the corresponding sets of attribute values, for the electronic devices detected within the communication network at the time;
• analyze the rogue classification information for the plurality of times to determine whether to modify the active rogue classification policies, wherein analyzing the rogue classification information for the plurality of times comprises analyzing, using a statistical machine learning algorithm, the respective rogue classifications and the corresponding sets of attribute values for the electronic devices for the plurality of times;
• generate, in response to determining to modify the active rogue classification policies, a recommended rogue classification policy;
• and
• transmit the recommended rogue classification policy to a network manager for evaluation prior to deployment of the recommended rogue classification policy for incorporating the recommended rogue classification policy as an active roque classification policy of the active rogue classification policies.

One or more non-transitory computer-readable storage media storing programming for execution by one or more processors, the programming comprising instructions to:

• obtain, at a plurality of times, rogue classification information for electronic devices detected within a communication network, the rogue classification information for each time of the plurality of times comprising:
• timestamp information identifying the time of the plurality of times;
• corresponding sets of attribute values for the electronic devices detected within the communication network at the time;
• and
• respective rogue classifications, as determined according to active rogue classification policies and the corresponding sets of attribute values, for the electronic devices detected within the communication network at the time;
• analyze the rogue classification information for the plurality of times to determine whether to modify the active rogue classification policies, wherein analyzing the rogue classification information for the plurality of times comprises analyzing, using a statistical machine learning algorithm, the respective rogue classifications and the corresponding sets of attribute values for the electronic devices for the plurality of times;
• and
• generate, in response to determining to modify the active rogue classification policies, a recommended rogue classification policy,
• wherein analyzing the rogue classification information using the statistical machine learning algorithm comprises:
• analyzing the corresponding attribute values for the electronic devices using a data correlation algorithm;
• and
• analyzing the corresponding attribute values for the electronic devices using a data prediction algorithm.