Preventing leakage of selected information in public channels
AssigneeInternational Business Machines Corporation
InventorsStefano Braghin, Ioannis Gkoufas, Valentina Rho
Life of this patent
Estimating the term…
Abstract
Various embodiments are provided for preventing disclosure of confidential data in a computing environment are provided. Data may be inspected prior to publication to a communication channels. Selected portions of the data may be extracted. The selected portions of the data may be filtered according to degree of appropriateness defined in one or more publishing policies or rules prior to sending the filtered data to the communication channel.
Claims20
A method, by a processor, for preventing disclosure of confidential data in a computing environment, comprising:
- executing machine learning logic to learn a degree of appropriateness of data based on one or more publishing policies or rules for publishing the data to a communication channel, wherein learning the degree of appropriateness includes using the one or more publishing policies or rules for publishing the data to infer the degree of appropriateness of the data with specific respect to transmitting the data through the communication channel, versus the degree of appropriateness with respect to transmitting the data through alternative communication channels, notwithstanding whether the communication channel nor information in the data explicitly is referenced in the one or more publishing policies or rules for publishing, and wherein inferring the degree of appropriateness of the data further includes identifying that the information in the data is of a particular composition able to be deduced as sensitive data;
- inspecting the data prior to publication to the communication channel;
- extracting selected portions of the data;
- and
- filtering the selected portions of the data according to the degree of appropriateness prior to sending the filtered data to the communication channel.
A system preventing disclosure of confidential data in a computing environment, comprising:
- one or more computers with executable instructions that when executed cause the system to:
- execute machine learning logic to learn a degree of appropriateness of data based on one or more publishing policies or rules for publishing the data to a communication channel, wherein learning the degree of appropriateness includes using the one or more publishing policies or rules for publishing the data to infer the degree of appropriateness of the data with specific respect to transmitting the data through the communication channel, versus the degree of appropriateness with respect to transmitting the data through alternative communication channels, notwithstanding whether the communication channel nor information in the data explicitly is referenced in the one or more publishing policies or rules for publishing, and wherein inferring the degree of appropriateness of the data further includes identifying that the information in the data is of a particular composition able to be deduced as sensitive data;
- inspect the data prior to publication to the communication channel;
- extract selected portions of the data;
- and
- filter the selected portions of the data according to the degree of appropriateness prior to sending the filtered data to the communication channel.
A computer program product for, by a processor, preventing disclosure of confidential data in a computing environment, the computer program product comprising a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:
- an executable portion that executes machine learning logic to learn a degree of appropriateness of data based on one or more publishing policies or rules for publishing the data to a communication channel, wherein learning the degree of appropriateness includes using the one or more publishing policies or rules for publishing the data to infer the degree of appropriateness of the data with specific respect to transmitting the data through the communication channel, versus the degree of appropriateness with respect to transmitting the data through alternative communication channels, notwithstanding whether the communication channel nor information in the data explicitly is referenced in the one or more publishing policies or rules for publishing, and wherein inferring the degree of appropriateness of the data further includes identifying that the information in the data is of a particular composition able to be deduced as sensitive data;
- an executable portion that inspects the data prior to publication to the communication channel;
- an executable portion that extracts selected portions of the data;
- and
- an executable portion that filters the selected portions of the data according to the degree of appropriateness prior to sending the filtered data to the communication channel.
Dependencies are inferred from the claim text.