System and methods for intelligent entity-wide data protection

A computer program product for intelligent entity-wide data classification and protection, the computer program product comprising at least one non-transitory computer readable medium stored on a storage device comprising computer readable instructions, the instructions comprising instructions that when executed cause at least one processing device to:

• receive a data set for analysis, wherein the data set comprises multiple data files;
• determine a data type and data format of the data set;
• determine an associated application identification, storage location, and current classification status for the data set;
• perform a sample scan of one or more of the multiple data files of the data set and determine a data field sampling, wherein the sample scan further comprises using affinity matching, context checking, or format matching to identify potentially sensitive information within the data fields;
• perform a full scan of the data set resulting from the sample scan and determine a classification of the data fields in each of the multiple data files via a machine learning engine;
• utilize a three-layered discovery method comprising a first pass metadata scan, a quick scan, and a deep scan to detect identifying characteristics of sensitive data or private data characteristics;
• based on the classification of the data fields in each of the multiple data files, determine one or more protection requirements and label the data fields with corresponding privacy levels;
• retrieve the associated application identification and generate a report of classifications and protection requirements for the application identification;
• and
• apply field-level encryption techniques to implement one or more protection requirements to protect sensitive data based on user access levels, wherein the one or more protection requirements further comprise a determination as to whether the data fields should be redacted, obfuscated, partially obfuscated, or encrypted according to one or more entity policies.

A computer implemented method for intelligent entity-wide data classification and protection, said computer implemented method comprising:

• providing a computing system comprising a computer processing device and a non-transitory computer readable medium, where the computer readable medium comprises configured computer program instruction code, such that when said instruction code is operated by said computer processing device, said computer processing device performs the following operations:
• receiving a data set for analysis, wherein the data set comprises multiple data files;
• determining a data type and data format of the data set;
• determining an associated application identification, storage location, and current classification status for the data set;
• performing a sample scan of one or more of the multiple data files of the data set and determine a data field sampling, wherein the sample scan further comprises using affinity matching, context checking, or format matching to identify potentially sensitive information within the data fields;
• performing a full scan of the data set resulting from the sample scan and determine a classification of the data fields in each of the multiple data files via a machine learning engine;
• utilizing a three-layered discovery method comprising a first pass metadata scan, a quick scan, and a deep scan to detect identifying characteristics of sensitive data or private data characteristics;
• based on the classification of the data fields in each of the multiple data files, determining one or more protection requirements and labelling the data fields with corresponding privacy levels;
• retrieving the associated application identification and generate a report of classifications and protection requirements for the application identification;
• and
• applying field-level encryption techniques to implement one or more protection requirements to protect sensitive data based on user access levels, wherein the one or more protection requirements further comprise a determination as to whether the data fields should be redacted, obfuscated, partially obfuscated, or encrypted according to one or more entity policies.