Resource Center Content Type Case Studies & Customer Testimonials Compliance Guides Datasheets eBooks and Whitepapers Infographics Reports SOC Threat Intel Videos Webinars Topics Application Security AWS Security Compliance for the Cloud Container Security DevSecOps Machine Learning Security Research Evaluating An ML-based Cloud Security Solution For modern cloud environments and for on-premises infrastructure making the transition, comprehensive cloud security coverage requires behavior-based alerting rules, ML-generated insights, and human expertise. These elements must work together to deliver high-precision detection that optimizes a security organization’s ability to respond to both known and unknown threats. This ebook explores the criteria for assessing a ML-based security solution and how Threat Stack’s human-machine feedback loop approach to cloud security enables security organizations to realize the promise of intelligent security through preserving the value of detailed telemetry while automating human-intensive triage work — ultimately helping security teams more efficiently and effectively protect their critical infrastructure and applications. Share this eBook