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WiP: AABAC - Automated Attribute Based Access Control for Genomics Data

Published: 08 June 2022 Publication History

Abstract

The COVID-19 crisis and the subsequent vaccine development have demonstrated the potential of cutting-edge genomics research. However, the privacy of these sensitive pieces of information is an area of significant concern for genomics researchers. The current security models make it difficult to create flexible, automated, and secure data-sharing frameworks. These models also increase the complexity of adding or revoking access.
In this work, we investigate an automated attribute-based access control (AABAC) model for genomics data over Named Data Networking (NDN). AABAC secures the data itself rather than the storage location or transmission channel, provides automated data invalidation, and automates key retrieval and data validation while maintaining the ability to control access. When combined with NDN, we show that AABAC offers a secure and flexible access control framework.

Supplementary Material

MP4 File (SACMAT22-77wp.mp4)
This presentation video investigates an automated attribute-based access control (AABAC) model for genomics data over Named Data Networking (NDN).

References

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Cited By

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  • (2024)PRIDN: A Privacy Preserving Data Sharing on Named Data NetworkingIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.332766019(677-692)Online publication date: 1-Jan-2024
  • (2024)LIDC: A Location Independent Multi-Cluster Computing Framework for Data Intensive ScienceSC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1109/SCW63240.2024.00108(760-764)Online publication date: 17-Nov-2024

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  1. WiP: AABAC - Automated Attribute Based Access Control for Genomics Data

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      cover image ACM Conferences
      SACMAT '22: Proceedings of the 27th ACM on Symposium on Access Control Models and Technologies
      June 2022
      282 pages
      ISBN:9781450393577
      DOI:10.1145/3532105
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 08 June 2022

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      Author Tags

      1. CP-ABE
      2. genomics access control
      3. named data networking

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      • (2024)PRIDN: A Privacy Preserving Data Sharing on Named Data NetworkingIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.332766019(677-692)Online publication date: 1-Jan-2024
      • (2024)LIDC: A Location Independent Multi-Cluster Computing Framework for Data Intensive ScienceSC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1109/SCW63240.2024.00108(760-764)Online publication date: 17-Nov-2024

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