International Business Machines Corporation

Eric Jeffery

Shikhar Kwatra

Adam Lee Griffin

Aaron K Baughman

Saurabh Yadav

Gregory M J H Tkaczyk

Mariya Ali

Jason Horowitz

A computer captures a voice of a user. The computer determines a frequency spectrum and a voice pattern of the voice. The computer identifies one or more topics of the voice by transcribing the voice by a natural language processing. The computer identifies the user based on matching the frequency spectrum of the voice to the frequency spectrum of the conversation and the pattern of the voice to the pattern of the conversation when a conversation is intercepted and determines a trust score based on comparing the one or more topics to the one or more topics extracted from the conversation.

AI based system and method for corners of trust for a caller

A method, computer system, and a computer program product for filtering a phone call are provided. An incoming phone call to a phone is detected. Call metadata from the incoming phone call is received. The call metadata is compared to entries of a learned relationship filter. The entries of the learned relationship filter are obtained by monitoring behavior of a phone user on the phone during previous calls to the phone and application usage on the phone so that learned relationships to the phone user are identified and saved. The learned relationship filter provides a filtering response. The filtering response is performed to the incoming phone call.

Contextual call handling mechanism with learned relationship filter

An example operation may include one or more of receiving data from a plurality of sources associated with an entity, clustering the data into security-related topics, determining, via one or more machine learning models, maturity values of the entity for the security-related topics, respectively, and generating recommendations to improve the determined maturity values of the entity, wherein the maturity values relate to a level of security of the entity with respect to the security-related topics.

Cybersecurity maturity determination

An approach is provided for obscuring an individual likeness in a digital image based on a privacy policy. The approach identifies an individual whose likeness appears in a digital image taken by a digital camera with the digital image being stored. A determination is made, based on a privacy policy pertaining to the identified individual, whether to obscure the first individual's likeness in the digital image. Responsive to the determination being positive, the approach obscures the individual's likeness as it appears in the digital image.

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Monument, CO, United States of America

Eric Jeffery