Evolving to meet today’s business challenges requires organizations to support an increasingly diverse set of users, cloud environments, networks, and devices, with users both on premises and in remote locations. A security data lake improves visibility across the entire operation, providing a centralized solution for managing security. In this post, we’ll highlight the core benefits of using a security data lake and explore the role that security analytics plays in shielding businesses from cyberattacks.
Benefits of a Security Data Lake
Leveraging the power of the cloud, security data lakes offer a host of benefits for organizations that need to meet today’s security threats. Let’s look at five of the most significant:
Seamlessly blend security and contextual business data
Data platforms can be used to build a security data lake, which allows organizations to easily combine security data with contextual business data. With this broader context, security teams have greater visibility and deeper insight, making them better positioned to assess potential threats and address them.
Affordably store large volumes of security data long-term
Effective threat hunting often relies on large volumes of historical data. The high cost of data storage can discourage organizations from retaining security and business data from months or years ago, hampering the effectiveness of threat hunting efforts. Security data lakes offer low-cost cloud data storage, providing a cost-effective means for storing data for longer periods of time.
Speed up incident investigation
Efficient incident investigations often require significant computing resources. With support for a near-limitless number of concurrent users, cyber security teams can conduct investigations quickly without running into resource contention issues.
Advanced security analytics capabilities
Security data lakes allow security teams to collaborate with other professionals outside of the cyber security space, allowing them to access the expertise needed to conduct their work more effectively. Examples include engaging the expertise of security analysts as subject matter experts and working with data scientists on behavior models and machine learning analytics projects. Security teams can analyze data and build dynamic dashboards that display security metrics and risk indicators directly on the data platform.
Types of Security Analytics
Today’s organizations use security analytics to collect data and analyze it for correlations and patterns that may indicate the presence of a security threat. A well-rounded security analytics toolbox includes a combination of techniques such as the following:
This security analytics method analyzes user, device, and application data searching for unusual patterns of behavior that may indicate a potential security threat. One application of behavioral analytics is the detection of insider threats. Red flags such as unauthorized database requests or unusual patterns of email usage can be used to identify and address potential data theft from within an organization.
External threat intelligence
Receiving updated threat intelligence from third-party sources enriches the data an organization uses for its security analysis. Examples include the Department of Homeland Security’s Automated Indicator Sharing (AIS) or security data purchased from a third-party data marketplace.
Being able to trace an identified security threat’s entry point, actions taken, and potential for ongoing adverse action helps security teams neutralize ongoing threats and prevent similar attacks from happening in the future.
Predictive analytics has an important role to play in securing an organization from potential threats before they manifest. By applying statistical algorithms to historical security-related data, this analytics technique can predict the likelihood of future cyberattacks, helping teams identify and shore up potential vulnerabilities before they’re exploited.
Network analysis and visibility (NAV)
NAV analyzes application and end user network traffic, providing security teams with insight into how users and applications traffic is moving across a network.
Snowflake for Cyber Security and Security Data Lakes
The Snowflake Data Cloud unlocks powerful analytics, accelerates threat detection, and enables speedy incident investigations. Snowflake enables organizations to do away with the data silos perpetuated by legacy SIEM solutions with their limited storage capacity and high costs. With the Data Cloud, you can unify your logs and enterprise data in a single platform and store virtually unlimited amounts of “hot” data cost effectively for years. Snowflake users also benefit from a wide network of connected applications that provide out-of-the-box integrations, content, and visualizations to enable initiatives such as threat detection and response or risk and compliance.
Supercharge your advanced analytics tools by joining business and contextual data sets with your security data to achieve better fidelity and automation. Easily obtain dynamically updated threat intelligence from Snowflake Marketplace to accelerate threat hunting and investigations. And thanks to the Data Cloud’s elastic compute power and instant, on-demand scalability, you can stay focused on mission-critical activities without worrying about concurrency, resource contention, compute power, scalability, or cost.
See Snowflake’s cyber security capabilities for yourself. To give it a test drive, sign up for a free trial.