Web Reference: Michael Roytman, Chief Data Scientist, Kenna SecuritySecurity is overdue for actionable forecasts. Like predicting the weather, similar models should work fo... The goal of this empirical study was to investigate the performance of machine learning (ML)-based classifiers to predict the exploitability of a just-disclosed vulnerability, with the purpose of providing early feedback on the exploitability of new vulnerabilities in a realistic scenario. The Exploit Prediction Scoring System (EPSS) is a data-driven machine-learning model that estimates the probability that a published CVE will be exploited in the wild in the next 30 days.
YouTube Excerpt: Michael Roytman, Chief Data Scientist, Kenna Security Security is overdue for actionable
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