A Proposed Solution
Identifying Sensitive Information as a Safety Measure Against Privacy Vulnerabilities Associated With Optical Character Recognition
DOI:
https://doi.org/10.58445/rars.1846Keywords:
Optical character recognition, Sensitive Information, computer scienceAbstract
Optical character recognition (OCR) is a technology used to generate machine-readable text from images and documents; some OCR applications store extracted text in cloud storage, which has been proven to be not 100% secure for storing sensitive information. Therefore, items including sensitive information should not be processed and have their text extracted and stored to preserve the user’s security, which is not applicable unless sensitive data is identified first. Based on the conducted research about this problem, the previous efforts, and what is currently available, this paper proposes a solution of identifying items including sensitive information, and preventing OCR applications that store extracted text in cloud storage from extracting text out of items including sensitive information. This research also tests the validity of the major part of the proposed solution, which is identifying items including sensitive data in the first place. To test the ability to identify sensitive data, a MobileNet neural network was trained four times to determine whether items include sensitive data. The results of testing MobileNet after the last training session demonstrated the validity of identifying sensitive information at a reliable level of accuracy in a short time, indicating promising results for the proposed solution if applied to a real OCR application in the presence of simple coding, including if-else statements.
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