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The Promise and Reality of Cloud SecurityCloud security has been part of the cybersecurity conversation for years but has been on the sidelines for most enterprises.
The shift to remote work during the COVID-19 pandemic and digital transformation projects have moved cloud infrastructure front-and-center as enterprises address the associated security risks. This report - a compilation of cutting-edge Black Hat research, in-depth Omdia analysis, and comprehensive Dark Reading reporting - explores how cloud security is rapidly evolving.
Incident Readiness and Building Response Playbook
In this special report, learn the Xs and Os of any good security incident readiness and response playbook.
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1 Comments
User Rank: Apprentice
1/12/2018 | 4:37:14 PM
There are great places where ML is perfect for cybersecurity, but only as a part of the solution. The heart of our Constellation Analytics Platform is a Bayesian Inference Network built over years of research to reason like a team of cyber experts across weak inputs from disparate sensor systems. Some of those sensors need ML techniques to find the real signal, some don't - but they all come together in a BayesNet that prioritizes the threat and ultimately the risk.
We believe this is the only viable approach today given what you highlighted of lack of training data, and even if you had some training data, sensor outputs change frequently as the environment changes. Only with additional context can you uncover those malicious events that represent the highest risks.