Abstract: Various embodiments include systems and methods to implement predictive scan engine runtime durations by a security platform to predict runtime durations associated with computing resources. Predictive scan engine runtime durations may be determined by training a prediction model using a multiple linear regression analysis. For example, the security platform may determine a prediction model using training data that associates runtime durations with configuration inputs associated with a security service that operates with respect to a computing resource. Based on the prediction model, the security platform may determine a runtime estimate for a security service run that is configured similarly to a previous security service run used to train the prediction model.

Abstract: Various embodiments include systems and methods to implement predictive scan autoscaling by a security platform to predict scanning loads associated with computing resources. Predictive scan autoscaling may improve the security posture of computing resources by improving the speed by which a security platform may scan for threats of a cyberattack. The security platform may predict scanning loads based on data indicative of previous scanning loads over one or more periods of time. The security platform may combine predicted scanning loads with requests for scans received from various client networks.

Abstract: Various embodiments include systems and methods to implement predictive scan autoscaling using cluster-based prediction models by a security platform to predict scanning loads associated with computing resources. Predictive scan autoscaling using cluster-based prediction models may improve the security posture of computing resources by improving the speed by which a security platform may scan for threats of a cyberattack. The security platform may predict scanning loads based on data indicative of previous scanning loads over one or more periods of time for clusters of similar client networks, where similarity may be based on a comparison of deployment assets. The security platform may combine predicted scanning loads with requests for scans received from various client networks.

Abstract: Various embodiments include systems and methods to implement predictive scan autoscaling using cluster-based prediction models by a security platform to predict scanning loads associated with computing resources. Predictive scan autoscaling using cluster-based prediction models may improve the security posture of computing resources by improving the speed by which a security platform may scan for threats of a cyberattack. The security platform may predict scanning loads based on data indicative of previous scanning loads over one or more periods of time for clusters of similar client networks, where similarity may be based on a comparison of deployment assets. The security platform may combine predicted scanning loads with requests for scans received from various client networks.