Optimized verifiable fine-grained keyword search in dynamic multi-owner settings

Optimized verifiable fine-grained keyword search in dynamic multi-owner settings

Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) schemes support both fine-grained access control and keyword-based ciphertext retrieval, which make these schemes attractive for resource-constrained users (i.e., mobile or wearable devices, sensor nodes, etc.) to store, share and search enc...

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Bibliographic Details
Main Authors: MIAO, Yibin, DENG, Robert H., CHOO, DENG, LIU, Ximeng, NING, Jianting, LI, Hongwei
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2019
Subjects:
Access control
Ciphertext length
Cloud computing
Complexity theory
decryption overhead
Encryption
Keyword search
multi-keyword search
multi-owner setting
search result verification
Servers
Information Security
Online Access:https://ink.library.smu.edu.sg/sis_research/5074
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Institution: Singapore Management University
Language: English
Description
Summary:Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) schemes support both fine-grained access control and keyword-based ciphertext retrieval, which make these schemes attractive for resource-constrained users (i.e., mobile or wearable devices, sensor nodes, etc.) to store, share and search encrypted data in the public cloud. However, ciphertext length and decryption overhead in the existing CP-ABKS schemes grow with the complexity of access policies or the number of data users' attributes. Moreover, such schemes generally do not consider the practical multi-owner setting (e.g., each file needs to be signed by multiple data owners before being uploaded to the cloud server) or prevent malicious cloud servers from returning incorrect search results. To overcome these limitations, in this paper we first design an optimized Verifiable Fine-grained Keyword Search scheme in the static Multi-owner setting (termed as basic VFKSM), which achieves short ciphertext length, fast ciphertext transformation, accelerated search process, and authentic search result verification. Then, we extend the basic VFKSM to support multi-keyword search and multi-owner update (also called as extended VFKSM). Finally, we prove that the basic (or extended) VFKSM resists the Chosen-Keyword Attack (CKA) and external Keyword-Guessing Attack (KGA). We also evaluate the performance of these schemes using various public datasets.

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