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1. A system comprising: one or more computing devices comprising at least one processor and a memory configured to store a first machine learning model, a second machine learning model, and a third machine learning model, the processor configured to: receive, from a plurality of systems, data breach criteria and user activity data associated with a user, wherein the user accesses the user activity data in periodic operational work in conjunction with the plurality of systems; determine, using a first machine learning model, the data breach criteria, and the user activity data associated with the user, a plurality of data breach fields which are not intended to be accessible to the user; determine, using the first machine learning model, a respective information value associated with the user for each of the plurality of data breach fields; receive a query from the user to request access to a dataset associated with the plurality of systems; determine, using a second machine learning model, a structured intermediate representation of the query, wherein the structured intermediate representation of the query includes one or more data sensitive fields; determine, using a third machine learning model and the respective information value associated with the user for each of the plurality of data breach fields, a respective ranking value of the query for each of the one or more data sensitive fields; determine a data information loss value using the respective ranking value of the query for each of the one or more data sensitive fields; validate the query from the user to allow the user to access the dataset associated with the plurality of systems; and use one or more quantum computing resources to perform the first, second, and third machine learning models to evaluate data breach by studying data exploration patterns of the user, raise an alert of possible data breach to help to mitigate data breach through a preventive approach.
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