Security Analytics

As cybersecurity threats evolve, companies must adapt and rethink their security strategies. This means moving away from traditional technologies and towards new cybersecurity frameworks. One such framework is the NIST cybersecurity framework, which comprises five major functions:

  • Identify
  • Protect
  • Detect
  • Respond
  • Recover

These five functions are the pillars of a well-rounded and effective cybersecurity strategy that is designed to improve a company’s capacity to counteract threats. Security analytics technologies embody these principles and are focused on providing data to augment your ability to assess, analyze and manage security risks. As a result, organizations are increasingly turning to security analytics to help them implement and maintain security frameworks.

What Is Security Analytics?

The term “security analytics” does not refer to a particular technology or piece of software. There is no unified all-in-one security analytics tool or platform because every business has specific technical challenges and infrastructural vulnerabilities.

Instead, the term covers a set of methods and technologies for collecting and aggregating data in order to detect and block potential threats. For example, security analytics can include using behavior analysis tools for threat detection and security monitoring.

When choosing solutions for security analytics, start by gathering what security data you can get using your existing solutions. You should then match this data to the capabilities you need to support your security strategy, identify gaps in your current security analytics and choose solutions that cover those gaps.

The Primary Goal of Security Analytics

Companies have access to vast reserves of data generated by business applications and security solutions, including network activity and user activity monitoring solutions. The ultimate objective of security analytics tools is to transform this raw data into actionable insights that help you to do things like:

  • Proactively identify vulnerabilities and reduce risk
  • Detect threats quickly
  • Enable automated incident responses whenever possible

The Benefits of Data Analytics for Security

The key benefits of security data analytics include:

  • Stronger security
  • Improved forensic capabilities
  • Reliable regulatory compliance

Key Capabilities

Fundamental capabilities of security analytics include the following:

  • Searching for, collecting, storing and correlating security data across multiple sources, including:
    • Server and application logs
    • Network devices and network traffic logs
    • Physical servers
    • Endpoints
    • Virtual layer
    • Non-IT contextual data
    • Identity and access management tools
    • External threat intelligence sources
  • Behavioral analytics that identify patterns of user activity that differ from the baseline
  • Capability to identify and issue alerts concerning threat patterns
  • Threat analysis and a prioritization of data that is easy to read and comprehend Performing data searches after security breaches

Why Do Organizations Need Security Analytics?

The proliferation of increasingly advanced cybersecurity threats demands that organizations adopt an “assume compromise” mindset: the expectation that there are already attackers inside their IT systems. Traditional security tools like SIEMs and DLP used to be seen as a silver bullet against security threats. However, these products alone don’t provide all the security functions outlined by the NIST Cybersecurity Framework, and consequently should be paired with additional solutions. To elaborate, SIEM is only capable of providing the data you need for detecting and responding to threats, while DLP only helps in the identification of threats and protection against them. In the current cybersecurity context, these capabilities on their own are insufficient in protecting an entire infrastructure. Furthermore, without proper configuration and data governance processes, you risk drowning in a flood of false alerts. What an organization therefore needs is to build a strong security posture by implementing security analytics for the entire range of security functions: identification, protection, detection, response and recovery.

Common Use Cases

The most common use cases for security analytics are to:

To build a successful security analytics strategy, companies need to capture, describe and categorize their use cases and set clear goals for what they want to achieve. The more complex the use case, the harder it will be to recognize and predict threats — and the more sophisticated your strategy and security operations will need to be.

Key Challenges and How to Address Them

Building robust security analytics can require a significant upfront investment of time and resources. The technologies are diverse, and failure to configure them properly can lead to high rates of false positives and false negatives. If you are just starting, build on the capabilities you already have in your environment and look for solutions to address your top needs.

Here are some best practices to consider as you explore various security analytics tools and methods:

  • Define, prioritize and classify the key use cases for your organization.
  • Inventory the capabilities of your existing software.
  • Look for solutions that complement and extend your existing systems.
  • Start simple. Identify gaps in your current security analytics that interfere with your ability to improve your security posture by adopting one of the recommended security frameworks, such as the NIST Cybersecurity Framework. Look for a solution that will augment your current solutions and enable you to answer the following questions:
    • Which information is sensitive? Where does it resides? Is it at risk?
    • Who has access to sensitive data? How can I remediate excessive access?
    • Who is accessing sensitive data? Is there any improper privileged user activity?
    • Do I have to report a data breach? How can I make an informed decision more quickly?
    • In case of a security breach, what data would need to be recovered? How could incidents have been stopped?

Netwrix data security platform helps you at every step of the way in this process. It provides insights about your data and access to it, enables you to identify security gaps that may lead to a data breach, analyzes user behavior and detects threats. With the data the solution provides, you can streamline investigation, reduce response time against anticipated threats, determine the severity of a breach and turn all the information gathered from a breach into insights to fortify your security infrastructure against similar incidents in the future.

Product Evangelist at Netwrix Corporation, writer, and presenter. Ryan specializes in evangelizing cybersecurity and promoting the importance of visibility into IT changes and data access. As an author, Ryan focuses on IT security trends, surveys, and industry insights.