PROUD : verifiable privacy-preserving outsourced attribute based signcryption supporting access policy update for cloud assisted IoT applications

Belguith, S; Kaaniche, N; Hammoudeh, M; Dargahi, T

Abstract

The ever-growing number of Internet connected devices poses several cybersecurity risks. Most of the exchanged data between the
Internet of Things (IoT) devices are not adequately secured due to resource constraints on IoT devices. Attribute Based
SignCryption (ABSC) is a powerful cryptographic mechanism suitable for distributed environments, providing flexible access
control and data secrecy. However, it imposes high designcryption costs, and does not support access policy update (user
addition/revocation). This paper presents PROUD, an ABSC solution, to securely outsource data designcryption process to edge
servers in order to reduce the computation overhead on the user side. PROUD allows end-users to offload most of the
designcryption overhead to an edge server and verify the correctness of the received partially designcrypted data from the edge
server. Moreover, PROUD provides the access policy update feature with neither involving a proxy-server, nor re-signcrypting the
signcrypted message and re-distributing the users’ secret keys. The access policy update feature in PROUD does not affect the size
of the message received by the end-user which reduces the bandwidth and the storage usage. Our comprehensive theoretical and
experimental analysis prove that PROUD outperforms existing schemes in terms of functionality, communication and computation
overhead.

Citation

Belguith, S., Kaaniche, N., Hammoudeh, M., & Dargahi, T. (2020). PROUD : verifiable privacy-preserving outsourced attribute based signcryption supporting access policy update for cloud assisted IoT applications. Future Generation Computer Systems, 111, 899-918. https://doi.org/10.1016/j.future.2019.11.012

• Journal Article Type: Article
• Acceptance Date: Nov 8, 2019
• Online Publication Date: Nov 15, 2019
• Publication Date: Oct 1, 2020
• Deposit Date: Nov 11, 2019
• Publicly Available Date: Nov 15, 2020
• Journal: Future Generation Computer Systems
• Print ISSN: 0167-739X
• Publisher: Elsevier
• Volume: 111
• Pages: 899-918
• DOI: https://doi.org/10.1016/j.future.2019.11.012
• Publisher URL: https://doi.org/10.1016/j.future.2019.11.012
• Related Public URLs: https://www.sciencedirect.com/journal/future-generation-computer-systems