Cybersecurity programs these days are no longer focus on keeping intruders out of one’s networks. Gone were the days when the only solution was to build walls and tighter controls around information structures. Having threat deterrence that works against even detected, targeted threats is the best solution. It is imperative to have visibility into network activities and the ability to detect and trace attacks rapidly. To make this happen, companies must have strong data management in cybersecurity.
Importance of Data Management for Cybersecurity
In general, security teams underestimate the significance of data management in data protection and security analytics. Just like any application or function, weak data results in weak results. In cybersecurity, this means the most false positives for overburdened security analysis the higher risks of successful breaches and greater loss from every breach.
Best Practices for Data Management for Cybersecurity
To ensure strong data management for cybersecurity, companies must embrace the following best practices:
- Adoption of data management standards. It is important to establish a regularly updated card catalogue of data sources and the content of every source. It must have standards for naming, formatting, and combining. Big companies have been cataloguing data sources for business applications, data centre platforms, and email systems. Such discipline must be extended to security analytics.
- Use of the right tools and platform. Implementing a data management and analytics platform is a great way to empower security analysts to establish a complete picture instead of seeing that a breach took place. A platform that can correlate and optimise network communication data as well as enriched with business and security context allows analysts to see what the breach touched and what it did.
- Program flexibility. Both cybersecurity and data are moving targets. Criminals will consistently try to use new channels and attacks. Plus, data sources tend to evolve and multiply. For a data management program for cybersecurity to be successful, it should be in motion, can cope with the challenges and surprises, as well as comfortable with change.
- Establishment of executive sponsorship. Such sponsorship must be aligned with the counterparts elsewhere in the company to share best practices.
In terms of data management, the most important rule is to understand what analysts have to accomplish, not just the data they need. Also, companies must be ready for the growth of the number of data sources and the overall data volume. They must be able to work with any useful data that comes their way.