How to reduce false positives in cybersecurity?

Identifying and reducing false positives is crucial for any information security team. False alerts consume time and divert attention from real threats. How can this process be optimized to improve cybersecurity effectiveness?

Follow the strategies presented in this article.

What is a false positive?

In cybersecurity, a false positive occurs when defense systems, such as firewalls, antivirus, SIEM (Security Information and Event Management) solutions, or vulnerability scans, incorrectly flag legitimate activity as a threat.

False positives in information security can arise from various sources, such as:

• Detection rules that are too generic.
• Outdated threat signature databases.
• Improper security system configurations.
• Complex environments that generate atypical but legitimate behaviors.

In this scenario, it's important to note that while detecting potential risks is essential, false positive alerts consume computational resources and demand time from the security team. This excess of irrelevant alerts can lead to alert fatigue, compromising the response to critical incidents and exposing the organization to real threats.

Also read: What is a zero-click attack?

How can I reduce false positives in information security?

Completely eliminating false positives is not feasible, but there are effective strategies to minimize these incidents:

1. Use machine learning-based systems Machine learning (ML) solutions analyze behavior patterns over time and automatically adjust detection parameters. Unlike static rules, these systems continuously learn from data, identifying anomalies more accurately and reducing false positives by better distinguishing between legitimate behaviors and real threats.
2. Implement customized correlation rules Correlation rules determine which combinations of events should trigger alerts. In SIEM systems, for example, customizing these rules according to the typical behaviors of your organization prevents unnecessary alerts, ensuring that alerts are triggered only in genuinely suspicious situations, thus optimizing detection and response processes.
3. Enrich alerts with context More accurate alerts include relevant contextual information, such as:
   • Type of asset (server, workstation, mobile device);
   • Geographical location of the event;
   • User profile and activity history.
4. This contextualization allows for more precise analyses, making it easier to distinguish between normal behaviors and potential threats. Moreover, modern security systems can be integrated with asset databases and user directories to automatically provide this context.
5. Regularly test and adjust systems Frequent audits and vulnerability tests help identify flaws in detection systems and adjust configurations that might be generating false positives. Attack simulation tools (red teaming) and pentesting exercises provide valuable insights into the behavior of defense systems in controlled scenarios.
6. Prioritize alerts based on criticality Classifying alerts according to the criticality of assets and the potential impact helps focus on the most relevant incidents. Incident management systems allow you to set priorities and filter low-risk alerts, reducing the workload on the team and preventing false positives from diverting attention away from critical threats.
7. Automate responses to common incidents Automation is an effective strategy for dealing with frequent, low-risk alerts. Automated playbooks—standardized procedures for incident response—can be configured to perform automatic actions, such as temporarily blocking suspicious IPs or isolating compromised devices.
8. Use Bug Bounty programs Bug Bounty programs involve external experts who identify real vulnerabilities in the organization's systems. This practice helps differentiate genuine threats from false positives and provides continuous evaluation of defense mechanisms. With the insights gained, it's possible to adjust processes and configurations, strengthening security and improving detection accuracy.

Benefits of reducing false positives

Investing in strategies to reduce false positives brings several benefits to the organization:

• Greater operational efficiency: Security teams focus on real threats, increasing productivity.
• Cost reduction: Less time spent on false alarms means fewer resources wasted.
• Improved detection: Well-tuned systems increase the accuracy of threat identification.
• Healthier work environment: Reducing alert fatigue improves the well-being of security professionals.

False positives present a significant challenge in cybersecurity, but with strategic adjustments, automation, and the intelligent use of technology, these incidents can be reduced.

By implementing calibration practices, threat intelligence, and continuous training, your organization can optimize its security processes and maintain effective defense against real threats.

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