Efficient statistical techniques for detecting sensitive data

A computer-implemented method, comprising:

• obtaining a first data set indicating a distribution of one or more properties of a group of entities with respect to which targeted information presence analysis is to be performed;
• identifying one or more candidate attribute combinations from a plurality of attributes of records of a second data set, wherein individual ones of the candidate attribute combinations meet a data type similarity criterion with respect to a collection of data types of targeted information of entities of the group of entities;
• generating, corresponding to individual ones of the one or more candidate attribute combinations and the first data set, a collection of input features for a machine learning model, including at least one feature indicative of a statistical relationship between the distribution of the one or more properties and attribute values of an individual candidate attribute combination;
• and
• obtaining an indication of a predicted probability of a presence of targeted information in the second data set, wherein the predicted probability is obtained from the machine learning model using at least the collection of input features.

One or more non-transitory computer-accessible storage media storing program instructions that when executed on or across one or more processors cause the one or more processors to:

• identify one or more candidate attribute combinations from a plurality of attributes of records of a first data set, wherein individual ones of the candidate attribute combinations meet a data type similarity criterion with respect to a collection of data types of targeted information of entities of a group of entities;
• generate, corresponding to individual ones of the one or more candidate attribute combinations, a collection of input features for a machine learning model, including at least one feature indicative of a statistical relationship between (a) attribute values of the individual candidate attribute combination and (b) a second data set indicating one or more properties of a group of entities with respect to which targeted information presence analysis is to be performed;
• and
• obtain an indication of a predicted probability of a presence of targeted information in the first data set, wherein the predicted probability is obtained from the machine learning model using at least the collection of input features.