International Business Machines Corporation

Angineh Aghakiant

Roger C Raphael

Scott Schumacher

Rajesh M Desai

Mu Qiao

Ety Khaitzin

John Handy Bosma

Iun Veng Leong

Raj Desai

Immalla Grace Chen

Amitabha Das

Shalu Agrawal

Dynamic data dissemination is provided. A resolved data subject identifier corresponding to a data subject is selected from a set of resolved data subject identifiers existing in rows of a data asset. In response to determining that the resolved data subject identifier does not correspond to a right to forget list, it is determined that the resolved data subject identifier corresponds to a data subject request list. The rows are transformed to anonymize existing pseudo and personal identifiers in cells of the rows that are tied to columns associated with data classes for which specific consent dimensions have been indicated as revoked by the data subject.

Dynamic data dissemination under declarative data subject constraints

A method for microphone management is provided. The method includes receiving an enable secure audio indicator. In response to receiving the enable secure audio indicator, a set of computing devices are identified, and a communication is initiated to each device in the set of computing devices. The communication includes an instruction to disable a microphone associated with each respective device.

Management of computing device microphones

Provided is a method, computer program product, and system for automatically predicting unknown semantic data types in a rectangular dataset using a holistic knowledge of said dataset. A processor may receive one or more rectangular datasets, the one or more rectangular datasets comprising a plurality of columns having a set of known semantic data types. The processor may extract a set of features from the plurality of columns, where the set of features is used to determine a relationship among each column of the plurality of columns. The processor may construct a set of training data based on the extracted set of features. Using the training data, the processor may train a machine learning model to predict a semantic data type of a target column in a rectangular dataset having an unknown semantic data type.

Semantic data type classification in rectangular datasets

Predicting access impact of a plurality of rule changes on a corpus of information assets is provided. A set of affected rules in a new rule space for controlling access to the corpus of information assets is received. The set of affected rules is shredded to identify right-hand side terms contained in predication blocks of the set of affected rules. An enforcement knowledge graph is traversed to identify a set of hot information assets having same terms as the right-hand side terms of the set of affected rules. The set of hot information assets having the same terms as the right-hand side terms of the set of affected rules is added to a hash table of hot information assets.

Enforcement knowledge graph-based data security rule change analysis

A method, apparatus, system, and computer program product for evaluating enforcement decisions on an asset using a policy. Rules in the policy are applied by a computer system to the asset taking into account a context for a request to access the asset in response receiving to the request to access the asset, and wherein the rules in the policy determine whether access to the asset is allowed. A determination is made by the computer system as to whether a conflict is present in an initial decision made using the rules in the policy. A set of conflict resolution processes are applied by the computer system when the conflict is present such that a final decision is made on the request to access the asset.

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San Jose, CA, United States of America

Angineh Aghakiant