Systems, structures, and processes for interconnected devices and risk management

A system for providing entity risk score intelligence, comprising:

• at least one processor operable to execute computer program instructions;
• and
• at least one memory operable to store computer program instructions executable by said at least one processor, for performing:
• receiving baseline scoring data, associated with valid devices on a machine-machine network, at an entity warehouse, wherein the entity warehouse comprises a risk scoring and predictive analytics engine that provides entity risk score intelligence regarding an entity based in part of said baseline scoring data;
• <performing, at the entity warehouse, ongoing monitoring of (a) behavior and anomaly processes and data of said valid devices and (b) changes and behaviors processes and data of said valid devices, wherein each such processes and data impact the entity risk score intelligence;
• wherein the risk scoring and predictive analytics engine generates a risk score of the entity that is the total sum of all risk scores contributed by matching rules and generates a risk level, wherein the risk level is a mapping of the risk score to a value between 0 and 100;
• wherein the risk scoring and predictive analytics engine runs on a big data platform on a network and uses in-memory database processing;
• and
• providing system response and automatically generating real-time alerts when said risk score exceeds a defined threshold;
• wherein said generating a risk level uses entity groups, wherein the entity groups are entities that are grouped according to how their respective rules are related, wherein the entities satisfy rules from a single group, and wherein each entity group is compact and maximizes its relevance in the overall risk level determination.

A non-transitory storage medium having stored thereon a computer program comprising a program code for performing, when the computer program is executed on a computer, a method for providing entity risk score intelligence, comprising the steps of:

• receiving baseline scoring data, associated with valid devices on a machine-machine network, at an entity warehouse, wherein the entity warehouse comprises a risk scoring and predictive analytics engine that provides entity risk score intelligence regarding an entity based in part of said baseline scoring data;
• performing, at the entity warehouse, ongoing monitoring of (a) behavior and anomaly processes and data of said valid devices and (b) changes and behaviors processes and data of said valid devices, wherein each such processes and data impact the entity risk score intelligence;
• wherein the risk scoring and predictive analytics engine generates a risk score of the entity that is the total sum of all risk scores contributed by matching rules and generates a risk level, wherein the risk level is a mapping of the risk score to a value between 0 and 100;
• wherein the risk scoring and predictive analytics engine runs on a big data platform on a network and uses in-memory database processing;
• and
• providing system response and automatically generating real-time alerts when said risk score exceeds a defined threshold;
• wherein said generating a risk level uses entity groups, wherein the entity groups are entities that are grouped according to how their respective rules are related, wherein the entities satisfy rules from a single group, and wherein each entity group is compact and maximizes its relevance in the overall risk level determination.