Skip to main content

New Technologies for Storing and Transferring Personal Data

  • Conference paper
  • First Online:
Computational Science and Its Applications – ICCSA 2022 Workshops (ICCSA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13380))

Included in the following conference series:

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. General Data Protection Regulation – GDPR

    Google Scholar 

  2. NIST.SP.800-122. Guide to Protecting the Confidentiality of Personally Identifiable Information (PII)

    Google Scholar 

  3. NIST.SP.800-53. Security and Privacy Controls for Federal Information Systems and Organizations

    Google Scholar 

  4. 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

    Google Scholar 

  5. NIST PRIVACY FRAMEWORK 1.0 (PRAM): A tool for improving privacy through enterprise risk management

    Google Scholar 

  6. Data Leakage & Breach Intelligence. https://dlbi.ru/data-base-leaks-risks/

  7. Advanced Encryption Standard (AES)

    Google Scholar 

  8. 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)

  9. 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

    Chapter  Google Scholar 

  10. Nazym, K.: Methods and algorithms of barcoding for facial biometrics. Academic Dissertation Candidate of Engineering (2020)

    Google Scholar 

  11. 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.

    Google Scholar 

Download references

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).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nadezhda Shchegoleva .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

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

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-10542-5_47

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-10541-8

  • Online ISBN: 978-3-031-10542-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics