Machine learning

ESET has been working with machine learning algorithms to detect and block threats since 1990. Neural networks have been added to ESET product's detection engine in 1998.

Machine learning includes DNA detections, which use models based on machine learning to work effectively with or without cloud connection. Machine learning algorithms are also a vital part of the initial sorting and classification of incoming samples as well as of placing them on the imaginary “cyber-security map”.

ESET has developed its own in-house machine learning engine. It uses the combined power of neural networks (such as deep learning and long short-term memory) and a handpicked group of six classification algorithms. This allows it to generate a consolidated output and help correctly label the incoming sample as clean, potentially unwanted or malicious.

The ESET machine-learning engine is fine-tuned to cooperate with other protective technologies such as DNA, sandbox and memory analysis as well as with the extraction of behavioral features, to offer the best detection rates and lowest possible number of false positives.

Scanner configuration in ESET product's Advanced setup

ESET Windows endpoint products (from version 7.2)

 

SCHEME_MACHINE_LEARNING