What is security analytics?

Security analytics is an IT security process that analyzes available data to proactively prevent threats. It uses a combination of data collection, data aggregation, and AI to detect, identify, and defend against security threats.

Security analytics begins with data collection. Security platforms collect data from multiple sources, including on-site databases, cloud storage solutions, and edge computing applications. Next, is the platform aggregates and formats the data to ensure uniformity and interoperability. Finally, AI algorithms help to identify security trends and detect potential points of compromise.

This approach to cybersecurity is critical because it takes a proactive position with security threats. While traditional security tools such as firewalls and endpoint detection frameworks remain a key aspect of an organization’s security posture, these tools are limited in scope because they're naturally reactive. Teams can only take remedial action only after the system detects a threat.

By contrast, security analytics continuously evaluates both current and historical data to create a constantly updated threat profile that evolves as it receives new data. AI also plays a role: Machine learning capabilities enable security analytics platforms to combine disparate data sources and infer the type and frequency of potential threats. For example, say collected data shows an uptick in spam email volumes across multiple networks and services along with an increase in odd resource requests from users. Analytics tools can combine this information to pinpoint the scope of potential phishing efforts and suggest a course of action.