Abstract
Medical information about a person’s state of health, data on the diagnostic evaluation of his symptoms and complaints, especially those related to the field of mental health, require a special reliability of the information storage system, since their disclosure often leads to stigmatization of the patient. The article proposes a new technology for storing and transmitting personal data based on “zeroing the LSB layers” (least significant bit (LSB) component of the Red, Green and Blue color image) and filling these layers with QR-codes containing AES-encrypted personal medical data of the patient. Specified the approach allows you to remove personal data from open access, since the presence of a barcode in the LSB layer practically does not change the image, therefore, without knowing about its presence, an attacker will not pay attention to it, moreover, using existing applications or scanners, it is impossible to read information, and decryption of information is hindered by the lack of an encryption key.
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References
General Data Protection Regulation – GDPR
NIST.SP.800-122. Guide to Protecting the Confidentiality of Personally Identifiable Information (PII)
NIST.SP.800-53. Security and Privacy Controls for Federal Information Systems and Organizations
NIST.SP.800-37. Risk Management Framework for Information Systems and Organizations A System Life Cycle Approach for Security and PrivacyNIST.IR.8053. De-Identification of Personal Information
NIST PRIVACY FRAMEWORK 1.0 (PRAM): A tool for improving privacy through enterprise risk management
Data Leakage & Breach Intelligence. https://dlbi.ru/data-base-leaks-risks/
Advanced Encryption Standard (AES)
Kukharev, G.A., Kaziyeva, N., Tsymbal, D.A.: Barcoding technologies for facial biometrics: current status and new solutions. Sci. Tech. J. Inf. Technol. Mech. Opt. 18(1), 72–86 (2018). https://doi.org/10.17586/2226-1494-2018-18-1-72-86. (in Russian)
Kaziyeva, N., Kukharev, G., Matveev, Y.: Barcoding in biometrics and its development. In: Chmielewski, L.J., Kozera, R., Orłowski, A., Wojciechowski, K., Bruckstein, A.M., Petkov, N. (eds.) ICCVG 2018. LNCS, vol. 11114, pp. 464–471. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00692-1_40
Nazym, K.: Methods and algorithms of barcoding for facial biometrics. Academic Dissertation Candidate of Engineering (2020)
Patent of the Russian Federation No. 2714741. Method for generating a color QR-code according to images of faces and a device for its implementation. In: Kukharev, G.A., Kazieva, N., Shchegoleva, N.L.
Acknowledgments
The research is partially funded by the Ministry of Science and Higher Education of the Russian Federation as part of World-class Research Center program: Advanced Digital Technologies (contract No. 075-15-2020-903 dated 16.11.2020).
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Shchegoleva, N., Zalutskaya, N., Dambaeva, A., Kiyamov, J., Dik, A. (2022). New Technologies for Storing and Transferring Personal Data. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13380. Springer, Cham. https://doi.org/10.1007/978-3-031-10542-5_47
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DOI: https://doi.org/10.1007/978-3-031-10542-5_47
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