How Machine Learning for Cybersecurity Can Thwart Insider Threats

While there are innumerable cybersecurity threats, the end goal for many attacks is data exfiltration. Much has been said about using machine learning to detect malicious programs, but it's less common to discuss how machine learning can aid in identifying other types of notable threats. Critically, machine learning can be key in detecting one of the most insidious types of malicious actors – one with legitimate access to your network and systems. When properly trained, machine-learning algorithms can be used to identify insider threats and frauds before they become dangerous. When people hear the term "insider threat," many of them imagine an employee gone rogue, a disgruntled member of your team committing corporate espionage and leaking sensitive data or documents to competitors or criminals.