Imperva, Inc.

Aiah Lerner

Jonathan R Azaria

Ori Nakar

Nadav Avital

Matan Lion

According to some embodiments of the disclosure, a method includes receiving an electronic communication directed to a data resource, determining, by a machine learning (ML) web application firewall (WAF), an attack probability of the electronic communication based on a plurality of features, wherein subsets of the plurality of features are arranged in a plurality of feature groups, adjusting the attack probability based on respective feature weights of the plurality of feature groups.

Attack categorization based on machine learning feature contribution

A method by a network device for dynamically detecting emotional states of a user operating a client end station to interact with an application. The method includes receiving information regarding user inputs received by the client end station from the user while the user interacted with the application during a particular time period and determining an emotional state of the user based on analyzing the information and information regarding user inputs received by the client end station from the user while the user interacted with the application during one or more previous time periods that together with the particular time period form a time window.

Growing community of inventors

Tel Aviv, Israel

Aiah Lerner