Multiauthority Ciphertext Policy-Attribute-Based Encryption (MA-CP-ABE) with Revocation and Computation Outsourcing for Resource-Constraint Devices

Author:

Yan Xiaodan1ORCID,Tu Shanshan2ORCID,Alasmary Hisham3ORCID,Huang Fengming2

Affiliation:

1. School of Cyber Science and Technology, Beihang University, Beijing 100191, China

2. Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China

3. Department of Computer Science, College of Computer Science, King Khalid University, Abha 61421, Saudi Arabia

Abstract

Fog computing accredits by utilizing the network edge while still rendering the possibility to interact with the cloud. Nevertheless, the features of fog computing are encountering several security challenges. The security of end users and/or fog servers brings a significant dilemma in implementing fog computing. The computational power of the resources constrains Internet of Things (IoT) devices in the fog-computing environment. Therefore, an attacker can easily attack. The traditional methods like attribute-based encryption (ABE) techniques are inappropriate for resource-constraint devices with protracted computing and limited computational capabilities. In this regard, we investigate a multiauthority ciphertext policy-attribute-based encryption (MA-CP-ABE) method that enables multiauthority attribute revocation and computation outsourcing. Moreover, the encryption and decryption processes of resource-constraint IoT devices are outsourced to the fog nodes. In this way, it also reduces the computational burden of the resource-constraint IoT devices. Hence, we propose MA-CP-ABE for encryption and decryption, attribute revocation and outsourcing by reducing the computational burden and securing the system. We compare the computational offloading approach with the existing techniques to prove that the proposed approach outperforms the existing approaches. The proposed method reduces the operation time for the encryption and decryption process. We outsource cryptography operations to the fog node, reducing the end user’s computational cost. Eventually, simulated outcomes are used to assess the algorithm’s computational cost.

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

King Khalid University

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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