International Business Machines Corporation

Nicholas Bokun

Jacob Thomas Covell

Thomas Jefferson Sandridge

Zachary A Silverstein

Robert Huntington Grant

Jon Walheim

Clarissa Ho

Caroline Gaeta

Tyler Ems

Girish Ratnam

In an approach to dynamic mute control for web conferencing, one or more computer processors detect a start of a collaborative meeting. One or more computer processors receive a request to enable a dynamic mute feature for a microphone associated with a device of a user. One or more computer processors mute the microphone. One or more computer processors monitor the collaborative meeting to derive context. One or more computer processors determine a request for the user to participate in the collaborative meeting. One or more computer processors calculate an unmute confidence score based on the derived context.

Dynamic mute control for web conferencing

In an approach for dynamically adjusting parallel reality (PR) displays, a processor configures a viewing event. A processor receives data from data collecting devices located throughout a location of the viewing event. A processor classifies a crowd of the viewing event into at least two partitions using a learning-based neural network that ingests the data. A processor selects content to be displayed to each of the at least two partitions. A processor enables a PR display to simultaneously display the content to each of the at least two partitions.

Dynamic adjustment of parallel reality displays

Described are techniques for preserving data security for sensitive information. The techniques including identifying sensitive information in first audio data from a first client device. The techniques further comprise generating second audio data including hashed sensitive information, where the hashed sensitive information comprises an audio clip that replaces the sensitive information and that is based on the sensitive information. The techniques further comprise transmitting the second data including the hashed sensitive information to a second client device. The techniques further comprise receiving third audio data including the hashed sensitive information from the second client device. The techniques further comprise generating fourth audio data by replacing the hashed sensitive information with the sensitive information and transmitting the fourth audio data including the sensitive information to the first client device.

Intelligent hashing of sensitive information

A method, system, and computer program product for generating personalized security testing simulations is provided. The method identifies a user of a communications system. The user is associated with a user profile. The method generates a simulated attack communication based on the user, the user profile, and an attack personalization model. The simulated attack communication is transmitted to the user via the communications system. The method identifies a user response to the simulated attack communication and modifies the attack personalization model based on the user response.

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Stratford, NJ, United States of America

Nicholas Bokun