While most of the Machine learning articles focus on headline-grabbing topics like self-driving cars, GAN, and Image recognition, there are some other important areas that AI researchers and data scientists are working on.

This includes researches to solve anomaly detection, which helps in network security to preventing financial fraud protecting businesses, individuals, and online communities.

To help improve anomaly detection, Siddharth Bhatia (Ph.D. candidate) and his team at the National University of Singapore, have developed MIDAS (Microcluster-Based Detector of Anomalies) in Edge Streams. MIDAS is a new approach to anomaly detection that outperforms baseline approaches both in speed and accuracy. What makes MIDAS different from other available tools is its ability to detect these anomalies in real-time at speed greater than existing state-of-the-art models.