Accountable privacy preserving attribute based framework for authenticated encrypted access in clouds

Belguith, S; Kaaniche, N; Laurent, M; Jemai, A; Attia, R

Abstract

In this paper, we propose an accountable privacy
preserving attribute-based framework, called Ins-PAbAC, that
combines attribute based encryption and attribute based signature techniques for securely sharing outsourced data contents via
public cloud servers. The proposed framework presents several
advantages. First, it provides an encrypted access control feature,
enforced at the data owner’s side, while providing the desired
expressiveness of access control policies. Second, Ins-PAbAC
preserves users’ privacy, relying on an anonymous authentication
mechanism, derived from a privacy preserving attribute based
signature scheme that hides the users’ identifying information.
Furthermore, our proposal introduces an accountable attribute
based signature that enables an inspection authority to reveal
the identity of the anonymously-authenticated user if needed.
Third, Ins-PAbAC is provably secure, as it is resistant to both
curious cloud providers and malicious users adversaries. Finally,
experimental results, built upon OpenStack Swift testbed, point
out the applicability of the proposed scheme in real world
scenarios.

Citation

Belguith, S., Kaaniche, N., Laurent, M., Jemai, A., & Attia, R. (2020). Accountable privacy preserving attribute based framework for authenticated encrypted access in clouds. Journal of Parallel and Distributed Computing, 135, 1-20. https://doi.org/10.1016/j.jpdc.2019.08.014

• Journal Article Type: Article
• Acceptance Date: Aug 30, 2019
• Online Publication Date: Sep 17, 2019
• Publication Date: Jan 1, 2020
• Deposit Date: Nov 6, 2019
• Publicly Available Date: Sep 17, 2020
• Journal: Journal of Parallel and Distributed Computing
• Print ISSN: 0743-7315
• Publisher: Elsevier
• Volume: 135
• Pages: 1-20
• DOI: https://doi.org/10.1016/j.jpdc.2019.08.014
• Publisher URL: https://doi.org/10.1016/j.jpdc.2019.08.014
• Related Public URLs: https://www.sciencedirect.com/journal/journal-of-parallel-and-distributed-computing