Data security in large language models
AssigneeSap SE
InventorsSuresh Pasumarthi, Shiva Prasad Nayak
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Abstract
Certain aspects of the disclosure concern a computer-implemented method for improved data security in large language models. The method includes receiving a prompt query entered through a user interface, extracting a plurality of named entities from the prompt query and classifying the plurality of named entities into respective entity classes, tagging the plurality of named entities to be security compliant or security noncompliant based on the respective entity classes, and responsive to finding that one or more named entities are tagged to be security noncompliant, generating an alert on the user interface.
Claims20
A computer-implemented method for improved data security in large language models, the method comprising:
- receiving a prompt query entered through a user interface;
- extracting, in runtime, a plurality of named entities from the prompt query and classifying the plurality of named entities into respective entity classes;
- tagging, in runtime, the plurality of named entities to be security compliant or security noncompliant based on the respective entity classes;
- and
- responsive to finding that one or more named entities are tagged to be security noncompliant, generating an alert on the user interface.
A computing system for improved data security in large language models, the system comprising:
- memory;
- one or more hardware processors coupled to the memory;
- and
- one or more computer readable storage media storing instructions that, when loaded into the memory, cause the one or more hardware processors to perform operations comprising:
- receiving a prompt query entered through a user interface;
- extracting, in runtime, a plurality of named entities from the prompt query and classifying the plurality of named entities into respective entity classes;
- tagging, in runtime, the plurality of named entities to be security compliant or security noncompliant based on the respective entity classes;
- and
- responsive to finding that one or more named entities are tagged to be security noncompliant, generating an alert on the user interface.
One or more non-transitory computer-readable media having encoded thereon computer-executable instructions causing one or more processors to perform a method for improved data security in large language models, the method comprising:
- receiving a prompt query entered through a user interface;
- extracting, in runtime, a plurality of named entities from the prompt query and classifying the plurality of named entities into respective entity classes;
- highlighting, in runtime, on the user interface the plurality of named entities extracted from the prompt query;
- tagging, in runtime, the plurality of named entities to be security compliant or security noncompliant based on the respective entity classes;
- and
- responsive to finding that one or more named entities are tagged to be security noncompliant, generating an alert on the user interface,
- wherein the highlighting comprises generating a first visual cue for one or more named entities that are tagged to be security noncompliant and generating a second visual cue for remaining named entities that are tagged to be security compliant, the second visual cue being different from the first visual cue.
Dependencies are inferred from the claim text.