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Security Information and Event Management (SIEM) protects organizational assets in today's evolving cybersecurity landscape. As threats become more sophisticated, the importance of well-structured SIEM use cases cannot be underestimated. Dive in as we explore the modern approaches to building, organizing, and prioritizing SIEM use cases.
Read on to learn the right approach to building SIEM use casesGathering the Right Data for Meaningful Insights The top ten use cases you cannot afford to miss.
SIEM tools have seen a tremendous transformation in recent years. Their potential to detect even the smallest indicators of attack rests on the precision of their definitions and the quality of data they monitor. A robust SIEM security use case fundamentally pivots on three key pillars: insight, data, and analytics. Consider this as a harmonious triangle where insights are the outcomes, powered by analytics and driven by data. The relationship between these three elements is illustrated below.
When determining the data points for your cloud security, logs from your infrastructure often become the primary source. However, in the age of big data, not every piece of information is pertinent. Remember that ingesting irrelevant data into a SIEM tool can be costly. Opt for precision over volume, ensuring your security team can focus on the data truly essential for threat detection.
The integration of artificial intelligence and machine learning has significantly uplifted the analytics capabilities of SIEM. While complex models can now detect a sophisticated security threat, the power of simple analytics methods remains unmatched. A blend of these analytics can create a formidable defense mechanism against a potential cyber threat. Choose the simplest analytic method possible for a given use case.
Establishing a SIEM use case is just the beginning. Regularly revisiting and refining these cases ensures their relevance and efficacy. Adhering to guiding principles, such as the ones outlined in below, can significantly enhance the effectiveness of your SIEM use cases. See the table below.
In the world of SIEM technology, it's not about how many use cases you have but how relevant and effective they are. It's paramount to continually evaluate and prioritize them based on the dynamic risk landscape and organizational needs.
A given use case will typically follow the cycle outlined below. Each of these phases will require a different level of effort, depending on the size and maturity of your organization.
Once a use case retires from your SIEM solution, you must clean it up and update your use case catalog accordingly. Use cases can be easily categorized into hierarchical families for compliance, threat detection, and business-level applications. The below image illustrates Gartner’s approach to organizing SIEM use cases, rooted in their CARTA (Continuous Adaptive Risk and Trust Assessment).
When it comes to use cases, quality exceeds quantity. Having just a few strong use cases will be more effective than deploying many poorly built cases for your business needs. The drivers that may help you determine which use cases to prioritize are outlined below.
SIEM's capabilities have evolved, but the core principles remain consistent. Here are the top ten SIEM use cases that organizations should prioritize to maintain a robust security posture:
User credential compromise attempts: Ensure security incident detection mechanisms for attempts to compromise credentials—be it through brute force, pass-the-hash, golden ticket, or other methods. Prompt incident response on a data breach is vital.
Unwarranted privilege escalation: Monitor for anomalies suggesting unauthorized privilege escalations. When an account achieves unauthorized elevated access, the potential threat for misuse surges.
Account misuse: Often overlooked, dormant or inactive accounts are a gold mine for attackers. A comprehensive SIEM system ensures all accounts, active or not, are closely monitored for unusual activities.
Anomalies in privileged accounts: Given their elevated access rights, privileged accounts, like database admins, are prime targets. Harness log data analytics to detect and flag any unusual activities in these accounts.
Traffic to suspicious domains: Traffic to high entropy domains or those with short-lived registrations might hint at command and control servers used by attackers. SIEM should alert your security team of such traffic patterns.
Data loss prevention (DLP): Beyond just monitoring, SIEM should actively help prevent unauthorized data transfers, especially from critical endpoints or high-risk users. This includes those leaving the organization or flagged as potential risks.
System alterations: System changes, especially unauthorized ones, pose a severe threat. SIEM should promptly flag any unauthorized modifications, deletions, or alterations to configurations and logs.
Denial of Service (DoS) detection: With the rise of distributed denial-of-service (DDoS) attacks, SIEMs must evolve. They should monitor for traffic anomalies, malicious spikes, and suspicious requests indicative of a DoS attack.
Malware detection: With threats diversifying, SIEMs need to evolve beyond just signature-based detection. Integrating machine learning can enhance malware detection capabilities, providing real-time alerts.
Phishing detection: Phishing remains a persistent threat. SIEM should monitor and alert for suspicious activities suggesting potential phishing attempts, especially those targeting high-value information.
SIEM use cases play a pivotal role in today's complex cybersecurity landscape. While signature-based detection tools are our primary guards, catching known threats, they can't spot everything. That's where behavior-based tools step in, monitoring for unusual patterns and activities to detect novel threats. Think of it as having a security guard who recognizes known intruders and sensors that alert to suspicious movements. As businesses expand their networks and integrate advanced technologies in the evolving digital era, leveraging both aspects within SIEM ensures a more comprehensive and adaptive defense strategy.
Effective SIEM security use cases should focus on insight, data, and analytics. Use cases should be framed as analytics-driven insights and fueled by data.
Identify the right data sources for your SIEM. Not all data points are equally easy to integrate; only essential data should be managed for SIEM consumption.
Applying the right analytics to the collected data is crucial. Advanced analytics, like machine learning models, can enhance detection capabilities. However, simpler analytics methods, layered effectively, can also provide profound insights.
Some foundational principles ensure the efficiency and effectiveness of SIEM use cases, which must be followed from the start.
Use cases have lifecycles. Organizing, cataloging, reviewing, and optimizing them regularly is essential. Quality takes precedence over quantity in SIEM use cases.
SIEM's relevance in the cybersecurity domain is undeniable. With the rapid evolution of threats, it's not just about having an SIEM solution but optimizing it with the right use cases. Organizations can significantly bolster their security posture by embracing best practices and prioritizing use cases based on evolving threats and business requirements.
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