Trend Micro Predictive Machine Learning uses advanced machine
               learning technology to correlate threat information and perform in-depth file analysis
               to detect
               emerging unknown security risks through digital DNA fingerprinting, API mapping, and
               other file
               features. Predictive Machine Learning also performs a behavioral analysis on unknown
               or
               low-prevalence processes to determine if an emerging or unknown threat is attempting
               to infect
               your network.
Predictive Machine Learning is a powerful tool that helps
               protect your environment from unidentified threats and zero-day attacks.
Monitoring level is the degree of vigilance and strictness applied when detecting
               and responding to potential threats. Raising the level increases the sensitivity of
               the sensor, which increases the number of detections and alerts. Higher levels allow
               for more strict monitoring to help with situations like on-going threat investigations,
               but might generate a large number of nonessential logs and impact endpoint performance.
               Trend Micro recommends setting your monitoring level to 2 - Moderate to balance more
               relevant data with minimal impact on your endpoints. Some components used by higher
               monitoring levels are not available on all platforms.
| Detection Type | Description | 
| File | After detecting an unknown or low-prevalence file, the Trend Vision One Endpoint Security agent scans
                              the file using the Advanced Threat Scan Engine (ATSE) to extract file features and
                              sends the
                              report to the Predictive Machine Learning engine, hosted on the Trend Micro Smart
                              Protection
                              Network. Through use of malware modeling, Predictive Machine Learning compares the
                              sample to
                              the malware model, assigns a probability score, and determines the probable malware
                              type
                              that the file contains. If a functional Internet connection is unavailable, Predictive Machine
                              Learning automatically switches to the local model to provide constant unknown threat
                              protection against portable executable file threats. Depending on how you configure Predictive Machine Learning,
                              the Trend Vision One Endpoint Security agent
                              can attempt to  Quarantinethe affected file to prevent the threat from continuing to spread across your network. | 
| Process | After detecting an unknown or low-prevalence process,
                              the Trend Vision One Endpoint Security agent
                              monitors the process using the Contextual Intelligence Engine, and sends the behavioral
                              report to the Predictive Machine Learning engine. Through use of behavioral malware
                              modeling, Predictive Machine Learning compares the process behavior to the model,
                              assigns a
                              probability score, and determines the probable malware type the process is executing. Process detection also monitors script execution. If the
                              Contextual Intelligence Engine detects the execution of a suspicious script, Predictive
                              Machine Learning takes the configured action.  Predictive Machine Learning performs script blocking on the
                              following types of scripts: 
 Depending on how you configure Predictive Machine
                              Learning, the Trend Vision One Endpoint Security agent can  Terminatethe affected process or script and attempt to clean the file that executed the process or script. | 
 
		