System and method for implementing an artificial intelligence security platform
An embodiment of the present invention is directed to implementing an AI security platform that secures AI/ML models while keeping the configuration and implementation simple and streamlined. An embodiment of the present invention is directed to delivering visibility on AI models across an entire organization.
1. A system for implementing an artificial intelligence (AI) security platform, the system comprising:
a security center platform that serves as a central administrative software-as-a-service (SaaS) portal and collects and aggregates telemetry data across one or more AI implementations;
an interactive user interface that is configured to provide an analytics dashboard to track the one or more AI implementations and identify one or more adversarial security issues; and
a computer server that comprises a computer processor coupled to the interactive user interface and the security center platform wherein the computer server further comprises:
a data integrity module configured to provide data security and integrity in the one or more AI implementations and further provide adversarial protection;
a platform configuration monitoring interface configured to provide configuration monitoring associated with the one or more AI implementations; and
a model security module configured to provide insights on how one or more models are performing from a security perspective and further provide model awareness and abnormal model behavior analytics.
2. A system for implementing an artificial intelligence (AI) security platform, the system comprising:
a core security platform that comprises a computer processor that communicates with an API gateway, a container orchestration platform and at least one memory component;
an interface that communicates with one or more collector agents that receive data from one or more AI Services;
an asset discovery engine configured to collect metadata relating to one or more assets used for development and delivery of at least one AI pipeline, wherein the metadata relates to asset types, activity, data source and model; and
an analysis engine configured to monitor the one or more AI Services, the one or more assets and the at least one AI pipeline to identify potential threats from adversarial attacks by generating at least one security score that measures a security posture of an entity wherein the at least one security score is based on one or more of: security incidents, alerts and security findings.
3. The system of claim 2 , wherein the one or more collector agents operate in a customer environment.
4. The system of claim 2 , wherein the at least one memory component comprises at least one service bus, at least one cache and at least one database.
5. The system of claim 2 , wherein the at least one security score comprises: a model security score and a data security score.
6. The system of claim 2 , wherein the interface is configured to display a graphical representation of an organization pipeline.
7. The system of claim 2 , wherein the interface is configured to display a graphical representation of one or more: notable events and incidents.
8. The system of claim 2 , wherein the interface is configured to display one or more resilience recommendations.
9. The system of claim 2 , wherein the container orchestration platform comprises an operations management module, a reporting module, an inventory management module and an inventory monitoring module.
10. The system of claim 2 , wherein the at least one security score is calculated by individual assets, individual pipelines or multiple pipelines.
11. A method for implementing an artificial intelligence (AI) security platform, the method comprising the steps of:
communicating, via one or more collector agents, with one or more AI Services;
collecting, via an asset discovery engine, metadata relating to one or more assets used for development and delivery of at least one AI pipeline, wherein the metadata relates to asset types, activity, data source and model;
monitoring, via an analysis engine, the one or more AI Services, the one or more assets and the at least one AI pipeline to identify potential threats from an adversarial attack;
generating, via the analysis engine, at least one security score that measure a security posture of an entity wherein the at least one security score is based on one or more of: security incidents, alerts and security findings; and
providing, via an interface, security health data that represents the security posture of the entity wherein the security health data comprises the at least one security score.
12. The method of claim 11 , wherein the one or more collector agents operate in a customer environment.
13. The method of claim 11 , wherein the at least one memory component comprises at least one service bus, at least one cache and at least one database.
14. The method of claim 11 , wherein the at least one security score comprises: a model security score and a data security score.
15. The method of claim 11 , wherein the interface is configured to display a graphical representation of an organization pipeline.
16. The method of claim 11 , wherein the interface is configured to display a graphical representation of one or more: notable events and incidents.
17. The method of claim 11 , wherein the interface is configured to display one or more resilience recommendations.
18. The method of claim 11 , wherein the container orchestration platform comprises an operations management module, a reporting module, an inventory management module and an inventory monitoring module.
19. The method of claim 11 , wherein the at least one security score is calculated by individual assets, individual pipelines or multiple pipelines.
20. The method of claim 11 , wherein the one or more collector agents communicates the asset discovery engine and the analysis engine and further communicates with a core platform that comprises a computer processor that communicates with an API gateway, a container orchestration platform and at least one memory component.