Dealing With Data Overload: How to Take Control of Your Security AnalyticsDealing With Data Overload: How to Take Control of Your Security AnalyticsDealing With Data Overload: How to Take Control of Your Security Analytics

By Chris Scheels, Gurucul

Many organizations have made significant investments in the security tools they believe they need, but they still find themselves in a tough position. They've taken the time to invest in security analytics tools like Security Information and Event Management (SIEM ) or User and Entity Behavior Analytics (UEBA), but they can't use these tools effectively because the amount of data their enterprise generates is far greater than they can afford or effectively manage.

This can often lead them to refrain from bringing in specific data sources, which also means they're not maximizing their investment in the analytics tools. Massive data volumes and budget restrictions cause an imbalance: Security leaders must make difficult decisions between cost pressures (budget constraints, important data not ingested) and risk clarity (gaining full visibility). It can feel like a Catch-22.

Organizations face several challenges when it comes to security analytics . They need to find a better way to optimize high volumes of data, ensure they are getting maximum bang for the buck, and bring balance between cost and visibility. This allows more of the "right" or optimized data to be brought in for advanced analytics, filtering out the noise or useless data that isn't needed for analytics/machine learning. This is where data optimization — also called data pipeline management (DPM) — comes in, but few security analytics tools offer this option.

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Data Pipeline Management Challenges

The skyrocketing costs of security analytics tools like SIEM or UEBA come from the volume of data that enterprises are generating. This is much more than they can afford or allocate enough budget to get the data they need.

If you're a SOC manager, and your team is triaging alerts all day, perhaps you've got one full-time staffer who does nothing but look at Microsoft O365 alerts, and another person who just looks at Proofpoint alerts. The goal is to think about the bigger operational picture. When searching for a solution, it's easy to focus only on your immediate challenges and overlook future ones. As a result, you invest in a fix that solves today's problems but leaves you unprepared for the next ones that arise. You've shot yourself in the foot.

The collection, optimization, normalization, enrichment, routing, and retention of data can be difficult due to:

Overcoming Data Optimization Challenges

Organizations tend to buy different tools to solve different problems, when what they need is a data analytics platform that can apply analytics, machine learning, and data science to their data sets. That will provide the intelligence to make business decisions, whether that's to reduce risk or something else. Look for a tool, regardless of what it's called, that can solve the most problems for the least amount of money.

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A best practice is to use a solution that centralizes data in any format, for any destination, from any source, and across any data lake . Look for a library of pre-optimized, built-in data integrations and the ability to rapidly make custom connectors or request a guaranteed integration.

Once that is accomplished, it's easy to customize parsers and send data to the different third-party systems such as low-cost storage, data lakes, and SIEMs. Also, look for granular filtering features to lower log volume. This lowers costs, improves compliance, and improves performance. Companies can save, on average, 40% on their data costs immediately and up to 87% with tuning — depending on the source of the data.

Now more than ever, security teams need visibility and insight into access privileges and entitlements so they can manage and monitor identity-based threats (ITDR) across their organizations' environments. There is growing interest in ITDR and the importance of understanding the identities (both user and device), entitlements, and access behavior to add context to threats, detections, and investigations. This equates to even more data ingestion costs, so use DPM to reduce data volumes while maintaining security insights, which can help control costs and improve threat detection efficiency.

Related:Cracking the Code on Cybersecurity ROI

Goodbye, Data Overload

There's no doubt that security analytics is challenging, but there's a better way to optimize those volumes of data and ensure you're getting maximum bang for the buck. A unified security analytics platform with native data optimization capabilities not only enables data analytics' true potential but also provides a manageable, cost-effective solution to address the rising challenges that modern cybersecurity entails.

About the author:

Chris Scheels is vice president of product marketing at Gurucul .

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