Why Real-Time Analytics Is Important for Efficacy and Reduction of False Positives in a SIEM

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Legacy Security Information and Event Management (SIEM) systems trigger high false positives and negatives that put a huge burden on Security Operations teams. In fact, traditional SIEMs cannot track, analyze, or monitor every attribute of a potential cybersecurity event effectively and efficiently.

Notwithstanding advancements in cybersecurity, security professionals are unable to put an end to security breaches due to the exponential growth of the threat landscape, increased volume of collected and processed security data, and innumerable security alerts and false positives. To make things more efficient and better combat false positives, organizations prefer deploying an analytics-driven SIEM that focuses on prioritizing alerts to identify real threats.

Why Traditional SIEMs Cannot Effectively Deal with False Positives

The legacy SIEM is not as effective as it was a decade ago. One of the reasons is the sophistication and colossal surge of cybersecurity threats and attacks. Furthermore, traditional SIEMs weren’t optimized for threat detection and response. However, they have been good for log management and compliance requirements.

Moreover, a legacy SIEM system has weak (if any) analytics that are based on generic use cases and a generalized approach. Weak analytics, like rules, cause alert fatigue. Tuning and configuring generic analytics is a daunting task. They also drain your resources and cause vulnerabilities.

To deal with even a single false positive, legacy SIEMs require a fully staffed, 24/7 Security Operations Team to provide human analysis, response, and remediation that is out of the question for smaller organizations because they have talent shortages and budget constraints. Contending with too many false positives is an arduous task and, therefore, they are often disregarded. This is the reason critical alerts get missed and why victim organizations get compromised.

How Real-time Analytics Increases the Efficacy of Alerts

An analytics-driven SIEM is more efficient than a legacy SIEM. This modern SIEM provides you with real-time analytics whereby your company’s SIEM administrators and security analysts can increase the efficacy of security alerts in many ways, including:

  • Confirm security alerts and events
  • Gain context through threat intelligence
  • Include lessons from threat hunting

SIEM applies detection models and correlation rules to help SOC analysts understand whether the security alerts are triggered by anomalous or normal behavior. A modern SIEM’s real-time analytics should be effective enough to produce accurate results.

Security analytics provides better context for security alerts and automates incident investigation. In addition, analytics mitigates the sheer number of raw alerts into a manageable number of concise and categorized warnings. A modern SIEM powered by security analytics prioritizes alerts and then sends only the serious alerts to the security team. A fine-tuned analytics-driven SIEM correlates findings with various Threat Intelligence Feeds to identify even the most sophisticated threats.

The analytics-driven SIEM operates in real-time and, therefore, enables security operations teams to rank the smaller number of alerts by severity (e.g., low, medium, high, very high) utilizing a risk prioritization model. After that, appropriate action is taken based on the severity level of the alert.

How Real-time Analytics Can Assist in Automating Incident Investigation

As aforementioned, traditional SIEMs trigger a sheer number of security alerts, and investigating each of them manually is a daunting task. To combat this issue, security operations teams can use real-time analytics to automate incident investigation by providing contextualization to alerts.

An analytics-driven SIEM can enrich event data in real-time at the time of ingestion. This data encompasses user context, threat intelligence, geolocation, IP context, asset metadata, application information and so much more. Once data is ingested, security teams can use it in real-time threat analytics and for quick threat investigation and response processes. Rather than wasting time on false positives, security professionals can spend time investigating legitimate leads and cope with potential data breaches.

According to the IT best-practices group ONUG, analytics can eliminate 95% of false positives generated by some security tools. Security teams can utilize analytics to automate as much as 80% of the manual, repetitive tasks that waste security experts’ time every day.

The Future of Real-Time Analytics With SIEM

Real-time analytics is indispensable to transform the future of cybersecurity. Overwhelming security alerts are difficult to deal with using conventional SIEMs as they involve too much attention from human analysts. Unfortunately, the cybersecurity skills gap is already on the rise, and security leaders are looking for modern SIEM solutions to automate numerous manual, repetitive, and mundane tasks. Since real-time analytics in modern SIEMs can significantly reduce alert fatigue without too much involvement of manpower, organizations would prefer to deploy an analytics-driven SIEM in the future to save time and budget without the need to hire an additional workforce.

Modernize Your SOC with Gurucul Analytics-Driven SIEM

Gurucul Analytics-driven SIEM provides a powerful, proven alternative to legacy and next-gen SIEM products with the following differentiated capabilities:

  • Cloud-native / hybrid / easy on-prem implementations
  • Data pipelines with hundreds of agent/agentless/cloud connectors and the flexibility to ingest legacy/proprietary data
  • The ability to ingest unlimited historical and real-time data with long-term retention options
  • Guaranteed lower cost including predictable no infrastructure cost
  • Real-time high efficacy detection driven by the largest most comprehensive security content library including 2000+ machine learning models
  • Blazing fast contextual investigations with advanced data enrichment
  • AI-powered analyst-optimized contextual threat hunting
  • Advanced case management, data science, and risk-driven automated response
  • Gurucul STUDIO™, open analytics builder, to customize existing out-of-the-box models and security content along with drag and drop capability to build new models and policies
  • Identity and access monitoring and intelligence

The Way Forward

In the world of cyberwarfare, digital crimes are accelerating by leaps and bounds. Safeguarding sensitive data and protecting Personally Identifiable Information (PII) has become more important than ever to avoid compliance issues (e.g., GDPR, HIPAA, and so forth), financial losses, and reputational damage. For this to be done effectively, organizations must use modern security tools such as analytics-driven SIEM platforms that can increase the efficacy of security alerts, assist in automating incident investigation, and a lot more. If you are looking for a modern cybersecurity tool, Gurucul analytics-driven SIEM is your first and best bet.

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