Open Access

ARTICLE

Hidden Hierarchy Based on Cipher-Text Attribute Encryption for IoT Data Privacy in Cloud

Zaid Abdulsalam Ibrahim^1,*, Muhammad Ilyas²

1 Department of Electrical and Computer Engineering, Altinbas University, Istanbul, Turkey
2 Department of Computer Engineering, Altinbas University, Istanbul, Turkey

* Corresponding Author: Zaid Abdulsalam Ibrahim. Email:

Computers, Materials & Continua 2023, 76(1), 939-956. https://doi.org/10.32604/cmc.2023.035798

Received 04 September 2022; Accepted 17 April 2023; Issue published 08 June 2023

Abstract

Most research works nowadays deal with real-time Internet of Things (IoT) data. However, with exponential data volume increases, organizations need help storing such humongous amounts of IoT data in cloud storage systems. Moreover, such systems create security issues while efficiently using IoT and Cloud Computing technologies. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has the potential to make IoT data more secure and reliable in various cloud storage services. Cloud-assisted IoTs suffer from two privacy issues: access policies (public) and super polynomial decryption times (attributed mainly to complex access structures). We have developed a CP-ABE scheme in alignment with a Hidden Hierarchy Ciphertext-Policy Attribute-Based Encryption (HH-CP-ABE) access structure embedded within two policies, i.e., public policy and sensitive policy. In this proposed scheme, information is only revealed when the user’s information is satisfactory to the public policy. Furthermore, the proposed scheme applies to resource-constrained devices already contracted tasks to trusted servers (especially encryption/decryption/searching). Implementing the method and keywords search resulted in higher access policy privacy and increased security. The new scheme introduces superior storage in comparison to existing systems (CP-ABE, H-CP-ABE), while also decreasing storage costs in HH-CP-ABE. Furthermore, a reduction in time for key generation can also be noted. Moreover, the scheme proved secure, even in handling IoT data threats in the Decisional Bilinear Diffie-Hellman (DBDH) case.

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Keywords

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