Flink ML can be used to apply Machine Learning models on a stream of data and make decisions based on the output of the model. The same can also be applied to the problem of cloud security as well.

Cloud data collaboration platforms provide immense flexibility to store, share and manage access control. However, a lack of heuristic-based data breach detection leads to a serious security loophole in the current systems. With the amount of data growing at a staggering rate every day and increasing number of users accessing the resources, the problem gets even more critical.

This talk will provide an overview of how Apache Kafka and Flink ML can be used to apply various Machine Learning models to flag malicious access patterns mined from cloud activity events in Near Real-Time and how it can be scaled to high throughput systems.