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Open Access

ARTICLE

Searchable Attribute-Based Encryption with Multi-Keyword Fuzzy Matching for Cloud-Based IoT

He Duan, Shi Zhang*, Dayu Li
School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China
* Corresponding Author: Shi Zhang. Email: email

Computers, Materials & Continua https://doi.org/10.32604/cmc.2025.069628

Received 27 June 2025; Accepted 15 September 2025; Published online 16 October 2025

Abstract

Internet of Things (IoT) interconnects devices via network protocols to enable intelligent sensing and control. Resource-constrained IoT devices rely on cloud servers for data storage and processing. However, this cloud-assisted architecture faces two critical challenges: the untrusted cloud services and the separation of data ownership from control. Although Attribute-based Searchable Encryption (ABSE) provides fine-grained access control and keyword search over encrypted data, existing schemes lack of error tolerance in exact multi-keyword matching. In this paper, we proposed an attribute-based multi-keyword fuzzy searchable encryption with forward ciphertext search (FCS-ABMSE) scheme that avoids computationally expensive bilinear pairing operations on the IoT device side. The scheme supports multi-keyword fuzzy search without requiring explicit keyword fields, thereby significantly enhancing error tolerance in search operations. It further incorporates forward-secure ciphertext search to mitigate trapdoor abuse, as well as offline encryption and verifiable outsourced decryption to minimize user-side computational costs. Formal security analysis proved that the FCS-ABMSE scheme meets both indistinguishability of ciphertext under the chosen keyword attacks (IND-CKA) and the indistinguishability of ciphertext under the chosen plaintext attacks (IND-CPA). In addition, we constructed an enhanced variant based on type-3 pairings. Results demonstrated that the proposed scheme outperforms existing ABSE approaches in terms of functionalities, computational cost, and communication cost.

Keywords

Cloud computing; Internet of Things; ABSE; multi-keyword fuzzy matching; outsourcing decryption

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