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Major Role of Artificial Intelligence, Machine Learning, and Deep Learning in Identity and Access Management Field: Challenges and State of the Art

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Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022 (AISI 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 152))

Abstract

In order to meet the growing needs of organizations and individuals to access services and systems remotely, especially during the period of the covid-19 pandemic, the use of I&AM systems is increasingly widespread and optimized. Henceforth regulated by the GDPR, these systems must meet privacy requirements in order to strengthen citizens’ control over their personal data. Artificial Intelligence has proven its efficiency in offering methods to secure I&AM processes. In this direction, the main contributions of this paper consist in identifying the challenges facing I&AM process that are: identification, authentication, authorization, auditing/monitoring and accountability. Afterward, we study how these extracted challenges have been addressed by conducting a comprehensive survey of ML applications for the enhancement of I&AM’s five processes. Besides, we conduct an analysis of the studied solutions based on Cognitive Project Management for Artificial Intelligence (CPMAI) methodology. Finally, some future research directions are identified.

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Notes

  1. 1.

    https://csrc.nist.gov/CSRC/media/Publications/Shared/documents/itl-bulletin/itlbul2017-08.pdf NIST-IDG, 201 7.

  2. 2.

    https://professional.dce.harvard.edu/blog/business-applications-for-artificial-intelligence-an-update-for-2020/.

  3. 3.

    https://www.ibm.com/docs/en/ibm-mq/9.1?topic=mechanisms-identification-authentication.

  4. 4.

    https://www.ibm.com/docs/en/ibm-mq/9.1?topic=mechanisms-identification-authentication.

  5. 5.

    https://www2.deloitte.com/content/dam/Deloitte/us/Documents/risk/us-cloud-and-identity-and-access-management.pdf.

  6. 6.

    https://cs.stanford.edu/people/eroberts/courses/soco/projects/neural-networks/Neuron/index.htm.

  7. 7.

    https://cs.stanford.edu/people/eroberts/courses/soco/projects/neural-networks/Architecture/feedforward.html.

  8. 8.

    https://stanford.edu/~shervine/teaching/cs-230/.

  9. 9.

    http://www.cs.unibo.it/~danilo.montesi/CBD/Beatriz/10.1.1.198.5133.pdf.

  10. 10.

    https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/overview.

  11. 11.

    https://searchitchannel.techtarget.com/blog/Channel-Marker/Cognilytica-expands-on-CRISP-DM-model-for-AI-project-management.

  12. 12.

    https://www.cognilytica.com/cpmai-methodology/.

  13. 13.

    https://www2.deloitte.com/content/dam/Deloitte/us/Documents/audit/us-audit-deloitte-multi-factor-authentication.pdf.

  14. 14.

    https://datatracker.ietf.org/doc/html/rfc6749.

  15. 15.

    https://ahia.org/assets/Uploads/pdfUpload/WhitePapers/DefiningAuditingAndMonitoring.pdf.

  16. 16.

    https://distill.pub/2019/activation-atlas/.

  17. 17.

    https://distill.pub/2019/activation-atlas/.

  18. 18.

    https://gdpr-info.eu/.

  19. 19.

    https://techvisionresearch.com/wp-content/uploads/2018/01/The-Future-of-Identity-Management-2018-final.pdf.

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Author information

Authors and Affiliations

  1. STRS Lab/CEDOC 2TI Institut National Des Postes et Des Télécommunications, Rabat, Morocco

    Sara Aboukadri, Aafaf Ouaddah & Abdellatif Mezrioui

Authors
  1. Sara Aboukadri
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  2. Aafaf Ouaddah
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  3. Abdellatif Mezrioui
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Corresponding author

Correspondence to Sara Aboukadri .

Editor information

Editors and Affiliations

  1. Faculty of Computers Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava, Ostrava-Poruba, Moravskoslezsky, Czech Republic

    Václav Snášel

  3. International Center for Informatics Research, Beijing Jaiotong University, Beijing, China

    Mincong Tang

  4. College of Computer Science and Mathematics, Fujian University of Technology, Fuzhou, Fujian, China

    Tien-Wen Sung

  5. Fujian University of Technology, New Taipei, Taiwan

    Kuo-Chi Chang

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Aboukadri, S., Ouaddah, A., Mezrioui, A. (2023). Major Role of Artificial Intelligence, Machine Learning, and Deep Learning in Identity and Access Management Field: Challenges and State of the Art. In: Hassanien, A.E., Snášel, V., Tang, M., Sung, TW., Chang, KC. (eds) Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022. AISI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 152. Springer, Cham. https://doi.org/10.1007/978-3-031-20601-6_5

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