Security analytics is a combination of software, algorithms, and analytic processes used to detect potential threats to IT systems. The need for security analytics technologies is growing thanks to rapid advancements in malware and other cyberexploits.
Based on a Data Breach Investigations Report from Verizon, it takes a cybercriminal just minutes, even seconds, to steal sensitive data. But IT departments may not discover that breach for hours, sometimes even days or weeks. In many cases, the breach is discovered by an outside party, such as law enforcement or a customer.
Hackers are using innovative tactics to worm their way into IT systems. They leverage vulnerabilities in unpatched applications, create memory-resident scripts that can't be detected by malware scanners, and use phishing and other types social engineering to evade IT security systems.
The Verizon report found that nearly three-quarters (73%) of cyberattacks were by outsiders, half of whom were members of organized crime groups, and 12% were by hostile nations or government agencies. These creative approaches make it difficult for the average IT department to detect and block a potential attacker before they've made off with the data. It's only going to get worse, say analysts. Trellix's researchers predict that criminal organizations will consolidate into larger, stronger malware-as-a-service businesses with the resources to develop more sophisticated exploits.
To keep ahead of these professional criminal groups, traditional security solutions—antivirus software, firewalls, and intrusion detection and prevention systems—will require automation and real-time analysis to detect and prevent cyberattacks. That will require security analytics.
Security analytics applications use both real-time and historical data to detect and diagnose threats. Sources of information include:
Security analytics combines data from the various sources and looks for correlations and anomalies within the data.
A security analytics tool may use different methods for analyzing the data. These include traditional rules-based methods, as well as statistical analysis and machine learning. The application can also incorporate other components to automate and orchestrate events.
The main elements of a security analytics solution are summarized below.
These components help a security analytics application detect and prevent complex cyberattacks, including advanced persistent threats (APT). APTs are conducted in stages, each of which might seem innocuous, but that together can create a breach. APTs are often called blended attacks, as they use multiple tactics. An APT may start with an email containing a malicious attachment or link. Once an endpoint is infected, the attacker can gain access to other systems.
Security analytics tools can deliver benefits for:
Security analytics can help an IT department make sense of the volumes of data flowing in and out of its network and to quickly detect potential threats. By providing real-time intelligence and a historical record of past threats, a security analytics application can protect an organization from a potentially costly data breach or cyberattack. The safety of an organization's data and IT systems increasingly depends on having an effective security analytics solution.