Efficient Multikeyword Searchable and Verifiable Data Sharing for Cloud-Edge Collaboration Intelligent Transportation Systems

Intelligent transportation systems (ITSs) are essential for the development of future smart cities. They can improve traffic management, mitigate urban congestion, and provide extensive social services by disseminating traffic data collected from vehicles. To facilitate the exchange of sensory data with other vehicles and alleviate the local storage load, sensory data from vehicles is frequently uploaded to cloud or edge servers. However, current ITS data sharing frameworks exhibit certain security vulnerabilities. In particular, they are unable to support secure multikeyword searches or ensure verifiable retrieval of encrypted information. Moreover, some of the schemes cannot ensure the integrity of the retrieved data. Therefore, we propose an efficient multikeyword searchable and verifiable data sharing (EMKV-ABSE) for cloud-edge collaboration ITS. EMKV-ABSE integrates a multikeyword attribute-based searchable encryption (ABSE) scheme and a tamper-proof consortium blockchain (BC). In EMKV-ABSE, we store the keyword indexes and ciphertext hashes of the shared data on the BC, which can ensure the integrity and authenticity of the data. Meanwhile, to avoid security and trust issues associated with central search cloud servers, smart contracts are utilized to perform multikeyword searches and verify retrieval results. Furthermore, the EMKV-ABSE scheme outsources the complex computational tasks in encryption and decryption to edge servers, which realizes lightweight computation for resource-constrained users. The security analysis proves that EMKV-ABSE satisfies the indistinguishability under the chosen plaintext attack (IND-CPA) and the chosen keyword attack (IND-CKA) in the standard model. Performance evaluation shows the efficiency and practicability of our scheme.

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Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-01-16
DOI
https://doi.org/10.1109/jiot.2025.3529934
Citations
5
Primary Topic
Cognitive Computing and Networks
Type
article
Field-Weighted Citation Impact
12.40

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article

Efficient Multikeyword Searchable and Verifiable Data Sharing for Cloud-Edge Collaboration Intelligent Transportation Systems

Shan Jiang, Peng Liu, Yiting Chen, Qian He
5 citations
IEEE Internet of Things Journal
Cognitive Computing and Networks
12.40
article

Efficient Multikeyword Searchable and Verifiable Data Sharing for Cloud-Edge Collaboration Intelligent Transportation Systems

Shan Jiang, Peng Liu, Yiting Chen, Qian He
article en
5 citations

Abstract

Intelligent transportation systems (ITSs) are essential for the development of future smart cities. They can improve traffic management, mitigate urban congestion, and provide extensive social services by disseminating traffic data collected from vehicles. To facilitate the exchange of sensory data with other vehicles and alleviate the local storage load, sensory data from vehicles is frequently uploaded to cloud or edge servers. However, current ITS data sharing frameworks exhibit certain security vulnerabilities. In particular, they are unable to support secure multikeyword searches or ensure verifiable retrieval of encrypted information. Moreover, some of the schemes cannot ensure the integrity of the retrieved data. Therefore, we propose an efficient multikeyword searchable and verifiable data sharing (EMKV-ABSE) for cloud-edge collaboration ITS. EMKV-ABSE integrates a multikeyword attribute-based searchable encryption (ABSE) scheme and a tamper-proof consortium blockchain (BC). In EMKV-ABSE, we store the keyword indexes and ciphertext hashes of the shared data on the BC, which can ensure the integrity and authenticity of the data. Meanwhile, to avoid security and trust issues associated with central search cloud servers, smart contracts are utilized to perform multikeyword searches and verify retrieval results. Furthermore, the EMKV-ABSE scheme outsources the complex computational tasks in encryption and decryption to edge servers, which realizes lightweight computation for resource-constrained users. The security analysis proves that EMKV-ABSE satisfies the indistinguishability under the chosen plaintext attack (IND-CPA) and the chosen keyword attack (IND-CKA) in the standard model. Performance evaluation shows the efficiency and practicability of our scheme.

IEEE Internet of Things JournalVol. 12(11)
Hong Kong Polytechnic University (HK), Guilin University of Electronic Technology (CN)
Natural Science Foundation of Guangxi Zhuang Autonomous Region, National Natural Science Foundation of China
Industry, innovation and infrastructure
Openalex Percentile: Top 2%
Cognitive Computing and Networks
12.40
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