Reducing False Positives in Cybersecurity: A Milestone in Detection Accuracy

 The article discusses the growing issue of false positives in cybersecurity, particularly when monitoring systems flag non-malicious activities as threats. The focus is on solutions like the FP Remover tool developed by GitGuardian. This tool uses machine learning to filter out false alarms, improving detection accuracy. It is expected to reduce false positives by 50%, allowing security teams to focus on real threats. The machine learning model behind FP Remover was designed to identify the most obvious false positives without removing actual vulnerabilities. However, some small percentage of false positives still slip through

https://securityboulevard.com/2024/11/the-quest-to-minimize-false-positives-reaches-another-significant-milestone/

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