How do you design ML models for malicious network detection?

Machine Learning (ML) has found its place into cybersecurity a long time ago and usage of ML has given cybersecurity teams much-needed insights into the malware network and effective ways to curb cyber attacks. Most ML-based solutions are proprietary or designed for specific feature representations. In 2017, one of the most prominent credit reporting agencies (CRA) of the United States– Equifax, suffered a huge malicious attack that led to a data breach that is famous for all the wrong reasons. Personal and sensitive data worth 148 million was lost to a data breach. Such data breach and data risks are still prevalent irrespective of the endpoint protection and other monitoring techniques deployed by enterprises worldwide.