{"id":15838,"date":"2022-05-13T15:41:31","date_gmt":"2022-05-13T19:41:31","guid":{"rendered":"https:\/\/www.iri.com\/blog\/?p=15838"},"modified":"2022-05-13T16:01:34","modified_gmt":"2022-05-13T20:01:34","slug":"masking-pans-in-credit-card-images","status":"publish","type":"post","link":"https:\/\/beta.iri.com\/blog\/data-protection\/masking-pans-in-credit-card-images\/","title":{"rendered":"Masking PANs in Credit Card Images"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Abstract: <\/span><i><span style=\"font-weight: 400;\">Previously the <\/span><\/i><a href=\"https:\/\/www.iri.com\/blog\/data-protection\/darkshield-files-rpc-api\/\"><i><span style=\"font-weight: 400;\">DarkShield API for Files<\/span><\/i><\/a><i><span style=\"font-weight: 400;\"> could perform black-box redaction of primary account numbers (PANs, also known as CCNs) on credit cards only within defined areas in the image <\/span><\/i><span style=\"font-weight: 400;\"><span id='easy-footnote-1-15838' class='easy-footnote-margin-adjust'><\/span><span class='easy-footnote'><a href='https:\/\/beta.iri.com\/blog\/data-protection\/masking-pans-in-credit-card-images\/#easy-footnote-bottom-1-15838' title='&lt;span class=&quot;c9 c14&quot;&gt;Note that the DarkShield-Files API can also mask account and routing numbers in checks by supplying an API call with the coordinates where these numbers are located (the location of these numbers are always the same place). This can be seen in the following\u00a0&lt;\/span&gt;&lt;span class=&quot;c10 c9 c19&quot;&gt;&lt;a class=&quot;c7&quot; href=&quot;https:\/\/www.google.com\/url?q=https:\/\/www.iri.com\/blog\/test-data\/generating-test-data-in-pdf-and-images\/&amp;amp;sa=D&amp;amp;source=editors&amp;amp;ust=1652470831045065&amp;amp;usg=AOvVaw1PyJC8UM09vYCLQU2LvuF3&quot;&gt;article&lt;\/a&gt;&lt;\/span&gt;&lt;span class=&quot;c9 c13&quot;&gt;\u00a0where the DarkShield-Files API demonstrates the ability to mask credit card numbers and checking account and routing numbers by replacing the sensitive data in images with newly generated realistic data. Alternatively, the data can be simply redacted with a black box.&lt;\/span&gt;'><sup>1<\/sup><\/a><\/span><\/span><i><span style=\"font-weight: 400;\">. The accuracy of credit card number detection, and thus masking, however, has now been enhanced thanks to new OCR-A support in DarkShield. These addresses use cases where PAN locations vary among images, and when masked or synthetic PANs are needed in testing.<\/span><\/i><\/p>\n<h5><b>DarkShield and Optical Character Recognition<\/b><\/h5>\n<p><a href=\"https:\/\/www.iri.com\/products\/darkshield\"><span style=\"font-weight: 400;\">IRI DarkShield<\/span><\/a><span style=\"font-weight: 400;\"> is a solution built to provide data protection in semi-structured and unstructured data files. By searching for and identifying sensitive information in these types of files, DarkShield is able to provide precise masking control over files using various masking operations.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">It is important to note that unstructured data does not have to mean text in text files. Text in images and text in images embedded in documents are all viable targets for DarkShield. To scan and detect sensitive data in images the DarkShield API uses a technology called optical character recognition (OCR).<\/span><\/p>\n<h5><b>How OCR Works<\/b><\/h5>\n<p><span style=\"font-weight: 400;\">OCR works by processing a scanned image and analyzing the areas where there are black and white pixels in order to identify characters. Normally a process called thresholding occurs ahead of time to preprocess the image into a black and white image.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Each character is segmented into its own individual images. Then during the recognition phase, individual characters and words are identified based on a score assigned to them.<\/span><\/p>\n<h5><b>OCR and Credit Card Font<\/b><\/h5>\n<p><span style=\"font-weight: 400;\">Normally OCR relies on machine learning to recognize characters from groups of contours and shapes detected in an image. Machine learning is a powerful tool that provides an accurate and flexible method for character recognition.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">That said, machine learning is also limited by the trained models it uses. A broad but easy-to-understand example would be that a model trained on detecting cars cannot be used to detect a motorcycle.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Similarly, the Tesseract OCR models trained for detecting characters in images have challenges recognizing the characters of a credit card because they may be in a special font. This special credit card font is referred to as <\/span><i><span style=\"font-weight: 400;\">OCR-A<\/span><\/i><span style=\"font-weight: 400;\"> font. To deal with special fonts, models need to be trained with large data sets to learn how to recognize characters in special fonts.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A common alternative for recognizing characters in an exotic font is template matching. Template matching can be useful in certain situations, like in recognizing PANs, and is available as an alternative in the DarkShield API for detecting these characters in credit cards.<\/span><\/p>\n<h5><b>What is Template Matching?<\/b><\/h5>\n<p><span style=\"font-weight: 400;\">Template matching is a technique used to find matches or close matches in an image using a template image as the reference. In the context of OCR, template matching is used to help recognize optically processed characters in images.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This technique can be a very simple but effective method used for matching on handwriting or characters of a particular font.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-15843 aligncenter\" src=\"\/blog\/wp-content\/uploads\/2022\/05\/cc-sample.png\" alt=\"\" width=\"303\" height=\"191\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Template matching requires a template image containing characters in the target font. Using the template image as the base comparator, OCR will process the actual image to be parsed by using a sliding technique.\u00a0<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-15844 aligncenter\" src=\"\/blog\/wp-content\/uploads\/2022\/05\/ocr_a_reference-300x47.png\" alt=\"\" width=\"300\" height=\"47\" srcset=\"https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/ocr_a_reference-300x47.png 300w, https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/ocr_a_reference-768x121.png 768w, https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/ocr_a_reference.png 800w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p style=\"text-align: center;\"><i><span style=\"font-weight: 400;\">Reference image for OCR-A font used in template matching.<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">This process of sliding a template image from left to right, up to down, one pixel at a time, calculates how well a match has been discovered at each location. The index of the best match is recorded as the recognized character.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-15847 aligncenter\" src=\"\/blog\/wp-content\/uploads\/2022\/05\/SlidingAcrossImgCC-300x205.jpg\" alt=\"\" width=\"342\" height=\"234\" srcset=\"https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/SlidingAcrossImgCC-300x205.jpg 300w, https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/SlidingAcrossImgCC.jpg 694w\" sizes=\"(max-width: 342px) 100vw, 342px\" \/><\/p>\n<p style=\"text-align: center;\"><i><span style=\"font-weight: 400;\">Sliding across an image and matching based on the template image<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">To learn more about OCR template matching, follow this <\/span><a href=\"http:\/\/www.tjprc.org\/publishpapers\/2-14-1381407981-29.%20Optical%20character.full.pdf\"><span style=\"font-weight: 400;\">link<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<h5><b>Configuring the DarkShield-Files API Call<\/b><\/h5>\n<p><span style=\"font-weight: 400;\">To begin with, calls must be made to the DarkShield-Files API to create a <\/span><i><span style=\"font-weight: 400;\">search context<\/span><\/i><span style=\"font-weight: 400;\">, <\/span><i><span style=\"font-weight: 400;\">mask context<\/span><\/i><span style=\"font-weight: 400;\">, <\/span><i><span style=\"font-weight: 400;\">file search context<\/span><\/i><span style=\"font-weight: 400;\">, and <\/span><i><span style=\"font-weight: 400;\">file mask context<\/span><\/i><span style=\"font-weight: 400;\">. These contexts tell the API how it will search for PII, what masking operations should be applied on found PII, and special configurations to be used based on file types.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-15848\" src=\"\/blog\/wp-content\/uploads\/2022\/05\/ccsearchmaskcontext-226x300.png\" alt=\"\" width=\"513\" height=\"681\" srcset=\"https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/ccsearchmaskcontext-226x300.png 226w, https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/ccsearchmaskcontext.png 456w\" sizes=\"(max-width: 513px) 100vw, 513px\" \/><\/p>\n<p style=\"text-align: center;\"><i><span style=\"font-weight: 400;\">Search and mask context<\/span><\/i><i><\/i><\/p>\n<p><span style=\"font-weight: 400;\">In the search context shown above, a credit card matcher named \u201cCcnMatcher\u201d is defined and uses a regular expression pattern matcher to identify PANs. A mask context defines rules to indicate the masking function that will be used, and rule matchers to match rules with search matchers.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the setup above, a format-preserving encryption (FPE) rule called \u201cFpeRule\u201d is created and a rule matcher that pairs the \u201cCcnMatcher\u201d with the \u201cFpeRule\u201d is created and called \u201cFpeRuleMatcher\u201d.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-15849\" src=\"\/blog\/wp-content\/uploads\/2022\/05\/ccfilecontext-183x300.png\" alt=\"\" width=\"357\" height=\"585\" srcset=\"https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/ccfilecontext-183x300.png 183w, https:\/\/beta.iri.com\/blog\/wp-content\/uploads\/2022\/05\/ccfilecontext.png 296w\" sizes=\"(max-width: 357px) 100vw, 357px\" \/><\/p>\n<p style=\"text-align: center;\"><i><span style=\"font-weight: 400;\">File search context and file mask context<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">File search contexts and file mask contexts allow for file-type specific configurations to be passed as part of the context. In the setup above, there is a configuration for image files that specify that template matching will be used in conjunction with OCR.\u00a0<\/span><\/p>\n<h5><b>Results of Search and Masking<\/b><\/h5>\n<p><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-15843 aligncenter\" src=\"\/blog\/wp-content\/uploads\/2022\/05\/cc-sample.png\" alt=\"\" width=\"305\" height=\"192\" \/><\/p>\n<p style=\"text-align: center;\"><i><span style=\"font-weight: 400;\">Original credit card image<\/span><\/i><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-15850\" src=\"\/blog\/wp-content\/uploads\/2022\/05\/CCRedactedNo.png\" alt=\"\" width=\"305\" height=\"192\" \/><\/p>\n<p style=\"text-align: center;\"><i><span style=\"font-weight: 400;\">Credit card image with redacted numbers<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">From the comparison of the before and after images we can see the PANs have been identified and masked using black-box redaction. To view the full source code, see the credit card <\/span><a href=\"https:\/\/github.com\/TeamIRI\/darkshield-api-demos\/tree\/master\/pdf-image\/credit-card\"><span style=\"font-weight: 400;\">demo<\/span><\/a><span style=\"font-weight: 400;\"> hosted in IRI\u2019s GitHub repository. Contact <\/span><a href=\"mailto:darkshield@iri.com\"><span style=\"font-weight: 400;\">darkshield@iri.com<\/span><\/a><span style=\"font-weight: 400;\"> if you like more information.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Abstract: Previously the DarkShield API for Files could perform black-box redaction of primary account numbers (PANs, also known as CCNs) on credit cards only within defined areas in the image . The accuracy of credit card number detection, and thus masking, however, has now been enhanced thanks to new OCR-A support in DarkShield. These addresses<\/p>\n<div><a class=\"btn-filled btn\" href=\"https:\/\/beta.iri.com\/blog\/data-protection\/masking-pans-in-credit-card-images\/\" title=\"Masking PANs in Credit Card Images\">Read More<\/a><\/div>\n","protected":false},"author":152,"featured_media":15841,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[8],"tags":[25,1689,1687,1688,527,1386,1494,14,1305,13,1388,1624,438,529,437,143,1432],"class_list":["post-15838","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-protection","tag-big-data","tag-big-data-masking","tag-credit-card","tag-credit-card-image","tag-credit-card-numbers","tag-darkshield","tag-darkshield-api","tag-data-masking","tag-data-masking-tools","tag-data-protection-2","tag-iri-darkshield","tag-ocr","tag-parsing-unstructured-data","tag-primary-account-numbers","tag-processing-unstructured-data","tag-unstructured-data","tag-unstructured-data-masking"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Masking PANs in Credit Card Images - IRI<\/title>\n<meta name=\"description\" content=\"Masking Primary Account Numbers (PANs) in Credit Card Images. 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