Threat mitigation system and method

A computer program product comprising a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

• establishing connectivity with a plurality of security-relevant subsystems within a computing platform, the plurality of security-relevant subsystems including one or more of Content Delivery Network systems, Database Activity Monitoring systems, User Behavior Analytic systems, Mobile Device Management systems, Identity and Access Management systems, Domain Name Server systems, antivirus systems, operating systems;
• receiving a unified query concerning the plurality of security-relevant subsystems;
• parsing the unified query to define a plurality of queries for at least a portion of each of the security-relevant subsystems;
• executing the plurality of queries on the respective security-relevant subsystems;
• obtaining at least one security-relevant information set from each of the plurality of security-relevant subsystems, based upon, at least in part, the plurality of queries, thus defining a plurality of security-relevant information sets;
• processing the plurality of security-relevant information sets using artificial learning/machine learning to identify one or more commonalities amongst the plurality of security-relevant information sets, wherein processing the plurality of security-relevant information sets using artificial learning/machine learning to identify one or more commonalities amongst the plurality of security-relevant information sets includes:
• utilizing a decision tree based, at least in part, upon one or more previously-acquired security-relevant information sets;
• and
• defining an initial probabilistic model based upon, at least in part:
• the plurality of security-relevant information sets, and
• one or more user-specified probabilistic model variables;
• combining the plurality of security-relevant information sets to form an aggregated security-relevant information set for the computing platform based, at least in part, upon the one or more commonalities identified, wherein combining the plurality of security-relevant information sets to form the aggregated security-relevant information set for the computing platform based, at least in part, upon the one or more commonalities identified includes homogenizing the plurality of security-relevant information sets to form the aggregated security-relevant information set;
• enabling third-party access to the aggregated security-relevant information set;
• and
• generating a security profile based, at least in part, upon the aggregated security-relevant information set for the computing platform.

A computing system including a processor and memory configured to perform operations comprising:

• establishing connectivity with a plurality of security-relevant subsystems within a computing platform, the plurality of security-relevant subsystems including one or more of Content Delivery Network systems, Database Activity Monitoring systems, User Behavior Analytic systems, Mobile Device Management systems, Identity and Access Management systems, Domain Name Server systems, antivirus systems, operating systems;
• receiving a unified query concerning the plurality of security-relevant subsystems;
• parsing the unified query to define a plurality of queries for at least a portion of each of the security-relevant subsystems;
• executing the plurality of queries on the respective security-relevant subsystems;
• obtaining at least one security-relevant information set from each of the plurality of security-relevant subsystems, based upon, at least in part, the plurality of queries, thus defining a plurality of security-relevant information sets;
• processing the plurality of security-relevant information sets using artificial learning/machine learning to identify one or more commonalities amongst the plurality of security-relevant information sets, wherein processing the plurality of security-relevant information sets using artificial learning/machine learning to identify one or more commonalities amongst the plurality of security-relevant information sets includes:
• utilizing a decision tree based, at least in part, upon one or more previously-acquired security-relevant information sets;
• and
• defining an initial probabilistic model based upon, at least in part:
• the plurality of security-relevant information sets, and
• one or more user-specified probabilistic model variables;
• combining the plurality of security-relevant information sets to form an aggregated security-relevant information set for the computing platform based, at least in part, upon the one or more commonalities identified, wherein combining the plurality of security-relevant information sets to form the aggregated security-relevant information set for the computing platform based, at least in part, upon the one or more commonalities identified includes homogenizing the plurality of security-relevant information sets to form the aggregated security-relevant information set;
• enabling third-party access to the aggregated security-relevant information set;
• and
• generating a security profile based, at least in part, upon the aggregated security-relevant information set for the computing platform.