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Understanding Security Log Analytics vs. SIEM for Midsized Companies Targeted by Cybercriminals

Understanding Security Log Analytics vs. SIEM for Midsized Companies Targeted by Cybercriminals
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SecOps teams at midsize companies face a unique set of challenges when it comes to managing organizational cybersecurity.

Midsize companies (those with 100-999 employees and $50 million-$1 billion in annual revenue, according to Gartner) possess significant financial resources and valuable data that may be targeted by digital adversaries. But, unlike larger enterprise organizations, midsize companies can’t always afford to invest heavily in the expensive security tools and dedicated IT security staff needed to prevent cyber attacks. As a result, midsize companies have become a preferred target for cyber attacks, with a recent survey finding that 45% of midsize companies were targeted by cybercrime in the past year.

Choosing scalable, flexible, and cost-effective security tools is essential for midsize companies with limited resources to satisfy their security needs, and one of the most important decisions is whether to deploy a security log analytics platform or invest in a Security Information and Event Management (SIEM) solution.

In this blog, we’re taking a closer look at Security Log Analytics vs. SIEM to support security operations and threat hunting use cases. We’ll compare their core capabilities and costs before recommending which of these solutions we think is best for midsized SecOps teams working with a limited budget.

 

Log Analytics 2024

 

What is a Security Log Analytics Tool?

When comparing Security Log Analytics vs. SIEM tools, keep in mind that SecOps teams at midsized organizations need the ability to ingest, transform, index, search, and query security log data from throughout an organization’s IT infrastructure. Security log data includes:

  • Logs of security-related events, such as successful and failed login attempts, successful logins from unusual locations, password changes, privilege escalations, or account lockouts.
  • Logs from security tools like intrusion detection systems (IDS), intrusion prevention systems (IPS), firewalls, antivirus and anti-malware tools, identity and access management (IAM) systems, or extended detection and response (XDR) systems.

 

Centralize Data Cybersecurity

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Security log analytics tools collect and centralize log data from multiple sources, giving SecOps teams enhanced visibility of an organization’s security posture.

 

So, can you use log analytics for security operations and threat hunting? Core capabilities of a security log analytics tool include:

  • Log Data Collection - A security log analytics tool collects log data from an organization’s IT infrastructure and aggregate it to a single centralized location.
  • Log Data Normalization - A security log analytics tool normalizes log data into a common format to enable easier analysis.
  • Log Data Indexing and Storage - Log indexing is the process of sorting and structuring normalized log data to accelerate the querying process. Indexing can also allow the log data to be stored in a compressed format, enabling lower data storage costs and longer data retention periods.
  • Log Analytics and Querying - With a security log analytics tool, SecOps teams at midsized organizations can execute analytical queries on their log data to detect security threats or isolate potential vulnerabilities in their IT infrastructure.
  • Log Data Visualization - Security log analytics tools offer dashboarding and visualization tools that help SecOps teams interpret security data and communicate security concerns to internal stakeholders.

 

The Threat Hunter's Handbook: Using Log Analytics to Find & Neutralize Hidden Cyberthreats. Get you handbook.

 

Understanding Modern SIEM Solutions

A SIEM is a software-based security solution that delivers real-time security monitoring, cyber threat detection, and incident response orchestration capabilities. Early SIEM tools were developed by combining the features of two other types of security tools:

  • Security Information Management (SIM) tools that provide long-term storage and analytics for security log data.
  • Security Event Manager (SEM) tools that deliver real-time monitoring of security log data, security event correlation (SEC), and alerting capabilities.

Core capabilities of modern SIEM systems include:

  • Log Management - SIEM logging solutions collect and store security-related log data from on-prem and cloud data sources, including network devices, cloud-based applications and services, and security tools. They can normalize log data generated from disparate sources into a common format to enable easier analysis. SIEM tools can provide long-term storage of log data to enable historical trend analysis and regulatory compliance use cases, but this may be prohibitively costly for midsized companies.
  • Security Event Correlation and Log Analysis - SIEM tools analyze aggregated security and event logs in real time to detect Indicators of Compromise (IoCs) or anomalies that could signify a cyber attack. SIEM tools also perform real-time security event correlation, leveraging up-to-date threat intelligence to quickly detect and identify security threats.
  • Alerting - SIEM tools can be configured to automatically alert incident response teams via email or SMS when a potential security incident is identified.
  • Incident Response Orchestration - SIEM tools play an important role in orchestrating the incident response process. SIEM tools can be integrated with a Security Orchestration, Automation, and Response (SOAR) platform to accelerate incident response times and enable automated responses to cyber threats.
  • Reporting - SIEM tools offer visual dashboards and reports that help IT personnel understand and interpret security data.

 

Can You Use an ELK Stack as a SIEM? Check out this blog for a fresh take!

 

Security Log Analytics vs. SIEM for Midsized SecOps Teams

Security log analytics tools and SIEM solutions offer similar log management and analytics capabilities. But while SIEM tools offer more specialized security features like event correlation and incident response orchestration, security log analytics solutions are easier to deploy and operate, more versatile, and more cost-effective at scale compared to a SIEM.

While a robust SIEM platform is often the best choice for enterprise organizations with more intensive cybersecurity needs and higher budgets, security log analytics tools are frequently a better option for SMBs or cost-conscious enterprises that cannot justify investing in broader-based SIEM platforms.

The key advantages of choosing security log analytics are:

  • Versatility - Most security log analytics tools can also manage logs from IT infrastructure and applications. This supports ITOps and DevOps use cases in addition to security, which saves effort and reduces software license costs. SIEM solutions are narrower in scope with a strict focus on cybersecurity, so midsized companies may still need to deploy a log management or log analytics solution to support IT/DevOps use cases like cloud infrastructure and application monitoring.
  • Complexity - Security log analytics solutions are generally viewed as being easier to implement and operate than SIEM tools. While SIEM tools can require extensive set-up and ongoing tuning of correlation rules, security log analytics tools are often quick to deploy and their intuitive interfaces don’t require security expertise to understand threats and incidents.
  • Cost-Efficiency - Security log analytics tools can process and store a much higher volume of security logs at a lower cost compared to a SIEM solution. Superior cost-effectiveness at scale means that midsized companies using security log analytics can retain more of their security data for longer periods to support long-term analytics use cases like root cause and forensic analysis of security incidents or APT detection.

Given these advantages, security log analytics is a compelling option for organizations with tight budgets, limited staff, and basic security requirements that cannot justify investing in a SIEM platform. The following table compares security log analytics tools vs SIEM solutions.

 

Security Log Analytics Tools vs SIEM Solutions Compared

 

Although they support fewer functions and data types, a log analytics tool should be the foundation of a security stack. They are more scalable and more flexible while offering comparable log analytics functionality to SIEM platforms.

 

Achieve Cost Effective Security Log Analytics with ChaosSearch

When it comes to addressing their security needs, midsized organizations are beginning to recognize log analytics as an alternative to premium SIEM platforms that can also support ITOps and DevOps use cases.

ChaosSearch provides a versatile and cost-effective log analytics solution that can support use cases from security operations and fraud prevention to cloud infrastructure monitoring and user behavior insights.

Our Chaos LakeDB solution transforms your cloud object storage into a cloud-native security lake with unlimited hot data retention and built-in text search, SQL, and GenAI querying capabilities.

 

ChaosSearch Security Lake

 

By leveraging cost-effective cloud object storage alongside our proprietary log indexing technology, Chaos LakeDB offers midsized companies a versatile, easy-to-deploy, and cost-effective solution for enabling SecOps, ITOps, and DevOps use cases at scale.

 

Ready to learn more?

Read our white paper Security Log Analytics: Spotting and Stopping Bad Guys at Scale to learn more about how security log analytics offers a scalable and cost-effective alternative to SIEM solutions.

 

On-Demand Webinar. Security Log Analytics: Finding & Stopping Bad Guys at Scale. Watch Now.

About the Author, Dave Armlin

Dave Armlin is the VP Customer Success of ChaosSearch. In this role, he works closely with new customers to ensure successful deployments, as well as with established customers to help streamline integrating new workloads into the ChaosSearch platform. Dave has extensive experience in big data and customer success from prior roles at Hubspot, Deep Information Sciences, Verizon, and more. Dave loves technology and balances his addiction to coffee with quality time with his wife, daughter, and son as they attack whatever sport is in season. He holds a Bachelor of Science in Computer Science from Northeastern University. More posts by Dave Armlin