Patent Issued for Si data scanning process (USPTO 11074342)

2021 AUG 12 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent by the inventors Baumann, Andrew (Bloomington, IL, US), Boquist, William (Bloomington, IL, US), Bush, Richard James (Wylie, TX, US), Ha, Can Van (Bloomington, IL, US), Schierholz, Steve (Bloomington, IL, US), filed on August 14, 2017, was published online on July 27, 2021, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondents.

Patent number 11074342 is assigned to State Farm Mutual Automobile Insurance Company (Bloomington, Illinois, United States).

The following quote was obtained by the news editors from the background information supplied by the inventors: “Data scrubbing helps control risks relating to the collection and storage of personal and sensitive information regarding, for example, a business’s customers. Such risks become greater as corporate strategies increasingly exploit big data to realize revenue growth. Large companies sometimes store billions of lines of personal information in support of the services they provide and/or for exploitation in other ways. Many companies store such data in unstructured formats and/or in multiple formats. These factors contribute to massive and growing challenges for companies seeking to control risk using existing data scrubbing or scanning technologies.

“Current technology relies on pattern matching algorithms to detect sensitive information embedded in data files. For example, a delimited data item may be of the form XX/XX/XXXX-where “X” represents a number-and therefore may be flagged as potentially being a date of birth or another type of sensitive date. Flagged data items may be compiled for further review by humans to determine definitively whether they are truly “sensitive.” Current pattern matching methods require an exorbitant amount of computer memory and processing power, and are inefficient for processing large data stores. Moreover, current computer pattern matching systems are methodologically flawed, resulting in high rates of false positives.”

In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “Embodiments of the present technology relate to systems, computer-implemented methods and computer-readable media for scanning and/or scrubbing data of sensitive information and/or for preventing the introduction of unscrubbed data into computer files. Embodiments of the present inventive concept include a plurality of reference subcombinations for use in analyzing structured and/or unstructured subject files for sensitive information. More particularly, embodiments of the present inventive concept analyze a subject file to determine each instance in which two or more data elements of a reference subcombination are present in any one entry of the subject file.

“The advantages of the present inventive concept are significant. For example, the reduced and/or distributed processor load resulting from use of one embodiment of the present inventive concept can lead to significantly faster scanning of subject files. Moreover, embodiments of the present inventive concept enable data scanning and/or scrubbing with lower rates of false positives returned.

“In a first aspect, a computer-implemented method may be provided for scanning and/or scrubbing data, broadly comprising the following. The computer-implemented method may include accessing a reference table including a grid of data cells arranged in columns and rows and containing reference data elements. Each of the rows may relate to one of a plurality of data subjects. The method may also include generating a list of reference subcombinations. The list of reference subcombinations may be generated by designating a primary column for uniquely identifying the data subjects and generating a plurality of first preliminary reference subcombinations. Each of the first preliminary reference subcombinations may include reference data elements gathered from the primary column and a second column of a single row of the reference table. The method may also include accessing a subject file having a plurality of data entries. Each of the data entries may include a plurality of logically-related and delimited subject data elements. The method may also include identifying and generating a match record for each instance in which one of the data entries contains all reference data elements of one of the reference subcombinations. The computer-implemented method may include additional, less, or alternate actions, including those discussed herein, and may be implemented via one or more processors and/or computer-executable instructions stored on non-transitory computer-readable medium or media.

“In a second aspect, a system may be provided for scanning and/or scrubbing data, broadly comprising the following. The system may include an electronic memory configured to store a subject file having a plurality of data entries. Each data entry may include a plurality of logically-related and delimited subject data elements. The electronic memory may also be configured to store a reference table including a grid of data cells arranged in columns and rows and containing reference data elements. Each of the rows may relate to one of a plurality of data subjects. The system may also include an electronic processor in communication with the electronic memory. The electronic processor may be configured to generate a list of reference subcombinations by designating a primary column of the reference table for uniquely identifying the data subjects and generating a plurality of first preliminary reference subcombinations. Each of the first preliminary reference subcombinations may include reference data elements gathered from the primary column and a second column of a single row of the reference table. The electronic processor may also be configured to identify and generate a match record for each instance in which one of the data entries contains all reference data elements of one of the reference subcombinations. The system may include additional, less, or alternate functionality, including that discussed elsewhere herein.

“In a third aspect, a non-transitory computer-readable medium with an executable program stored thereon may be provided for scanning and/or scrubbing data, wherein, broadly speaking, the computer program may be configured to instruct an electronic processor to perform the following actions. The electronic processor may be instructed to access a reference table including a grid of data cells arranged in columns and rows and containing reference data elements. Each of the rows may relate to one of a plurality of data subjects. The electronic processor may also be instructed to generate a list of reference subcombinations by designating a primary column for uniquely identifying the data subjects and generating a plurality of first preliminary reference subcombinations. Each first preliminary reference subcombination may include reference data elements gathered from the primary column and a second column of a single row of the reference table. The electronic processor may also be instructed to access a subject file having a plurality of data entries. Each data entry may include a plurality of logically-related and delimited subject data elements. The electronic processor may also be instructed to identify and generate a match record for each instance in which one of the data entries contains all reference data elements of one of the reference subcombinations. The instructions may direct additional, less, or alternate functionality, including that discussed elsewhere herein.”

The claims supplied by the inventors are:

“1. A computer-implemented method for analyzing a subject file for sensitive information, the method comprising: accessing a reference table including a grid of data cells arranged in columns and rows and containing reference data elements, each of the rows relating to one of a plurality of data subjects; generating a list of reference subcombinations by- designating a primary column for uniquely identifying the data subjects; generating a plurality of first preliminary reference subcombinations, each first preliminary reference subcombination including reference data elements gathered from the primary column and a second column of a single row of the reference table; conducting a security review to identify a plurality of memory locations that are likely vulnerable to an attack vector; building the subject file by joining a plurality of precursor subject files stored at the plurality of memory locations; accessing the subject file having a plurality of data entries, each data entry including a plurality of logically-related and delimited subject data elements; identifying and generating a match record for each instance in which one of the data entries contains all reference data elements of one of the reference subcombinations, the match record being associated with the sensitive information; and revising the subject file based on the match record.

“2. The computer-implemented method of claim 1, wherein the identifying step includes comparing each of the reference subcombinations against each of the data entries, in each case by comparing each of the reference data elements of the reference subcombination against each of the subject data elements of the data entry at least until one of the reference data elements fails to match any subject data element of the data entry.

“3. The computer-implemented method of claim 1, comprising: generating a list of subject subcombinations by generating a plurality of first preliminary subject subcombinations, each first preliminary subject subcombination including two subject data elements from a single data entry; wherein the identifying step includes- combining the list of reference subcombinations with the list of subject subcombinations to generate a combined list, sorting the combined list to place like subcombinations together in groups, identifying groups that include at least one reference subcombination and at least one subject subcombination.

“4. The computer-implemented method of claim 3, wherein the first preliminary subject subcombinations include all possible two subject data element combinations of each of the data entries.

“5. The computer-implemented method of claim 4, wherein- the first preliminary reference subcombinations include all possible permutations of the reference data elements gathered from the primary column and the second column within each single row of the reference table, the first preliminary subject subcombinations include all possible two subject data element permutations of each of the data entries, the combined list is sorted to place like permutations together in groups.

“6. The computer-implemented method of claim 3, comprising assigning a higher order control character to each of the reference subcombinations and a lower order control character to each of the subject subcombinations, wherein the identification step includes- subsorting the subcombinations within each group in ascending order of control character and removing groups having a first-listed reference subcombination from consideration for generation of match records, subsorting the subcombinations within each group in descending order of control character and removing groups having a first-listed subject subcombination from consideration for generation of match records.

“7. The computer-implemented method of claim 1, comprising deleting duplicate first preliminary subject subcombinations to form the list of subject subcombinations.

“8. The computer-implemented method of claim 7, wherein first preliminary subject subcombinations are not considered to be duplicate if arising from different data entries.

“9. The computer-implemented method of claim 1, comprising-associating metadata with each reference subcombination including a unique row identifier and column labels for the primary column and the second column; associating metadata with each data entry including a unique data entry identifier, wherein each match record includes the metadata for each of the matched reference subcombination and data entry.

“10. The computer-implemented method of claim 9, wherein the metadata for each data entry includes a column label for each subject data element of the data entry.

“11. The computer-implemented method of claim 1, wherein generating the list of reference subcombinations includes- designating a second primary column for uniquely identifying the data subjects, generating a plurality of second preliminary reference subcombinations, each second preliminary reference subcombination including reference data elements gathered from the second primary column and another column of a single row of the reference table.

“12. The computer-implemented method of claim 11, further comprising ordering the match records by data entry in descending order of total number of reference subcombinations matched.

“13. The computer-implemented method of claim 1, wherein generating the list of reference subcombinations includes- for each reference data element of the first preliminary subcombinations, searching the subject file for a preliminary match, deleting each of the first preliminary subcombinations that includes a reference data element that does not have a preliminary match in the subject file.

“14. The computer-implemented method of claim 1, wherein-the plurality of data subjects includes a plurality of individual customers; the primary column includes reference data elements for one of: individual social security number, account number, customer id, and address; the second column includes reference data elements for one of: individual social security number, account number, customer id, address, date of birth, first name, middle initial, and last name.

“15. A system for analyzing a subject file for sensitive information, the system comprising: an electronic memory configured to store- the subject file having a plurality of data entries, each data entry including a plurality of logically-related and delimited subject data elements; a reference table including a grid of data cells arranged in columns and rows and containing reference data elements, each of the rows relating to one of a plurality of data subjects; an electronic processor in communication with the electronic memory, the electronic processor configured to- generate a list of reference subcombinations by- designating a primary column of the reference table for uniquely identifying the data subjects; generating a plurality of first preliminary reference subcombinations, each first preliminary reference subcombination including reference data elements gathered from the primary column and a second column of a single row of the reference table; build the subject file by joining a plurality of precursor subject files stored at a plurality of memory locations, the plurality of memory locations being identified to be likely vulnerable to an attack vector based upon a security review; identify and generate a match record for each instance in which one of the data entries contains all reference data elements of one of the reference subcombinations, the match record being associated with the sensitive information; and revise the subject file based on the match record.

“16. The system of claim 15, wherein the electronic processor is configured to- generate a list of subject subcombinations by generating a plurality of first preliminary subject subcombinations, each first preliminary subject subcombination including two subject data elements from a single data entry, wherein the identifying step includes- combining the list of reference subcombinations with the list of subject subcombinations to generate a combined list, sorting the combined list to place like subcombinations together in groups, identifying groups that include at least one reference subcombination and at least one subject subcombination.

“17. The system of claim 16, wherein- the electronic processor is configured to assign a higher order control character to each of the reference subcombinations and a lower order control character to each of the subject subcombinations, the identifying step includes- subsorting the subcombinations within each group in ascending order of control character and removing groups having a first-listed reference subcombination from consideration for generation of match records, subsorting the subcombinations within each group in descending order of control character and removing groups having a first-listed subject subcombination from consideration for generation of match records.

“18. The system of claim 15, wherein generating the list of reference subcombinations includes- designating a second primary column for uniquely identifying the data subjects, generating a plurality of second preliminary reference subcombinations, each second preliminary reference subcombination including reference data elements gathered from the second primary column and another column of a single row of the reference table.

“19. The system of claim 15, wherein the electronic processor is configured to build the subject file by joining a plurality of precursor subject files stored at a plurality of subject data locations identified in a security review as likely vulnerable to an attack vector.”

There are additional claims. Please visit full patent to read further.

URL and more information on this patent, see: Baumann, Andrew. Si data scanning process. U.S. Patent Number 11074342, filed August 14, 2017, and published online on July 27, 2021. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11074342.PN.&OS=PN/11074342RS=PN/11074342

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