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author:

Zhang, K. (Zhang, K..) [1] | Zhang, Y. (Zhang, Y..) [2] | Li, Y. (Li, Y..) [3] | Liu, X. (Liu, X..) [4] (Scholars:刘西蒙) | Lu, L. (Lu, L..) [5]

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Abstract:

Attribute-based searchable encryption (ABSE) is a promising encryption mechanism for sharing outsourced encrypted data in clouds, allowing fine-grained access control over data while searching for encrypted data. However, the access policy in the most existing ABSE schemes exists in plaintext, which could expose sensitive information about legitimate data users. Moreover, such schemes delegate complex search operations to a cloud server, which can lead to data tampering and even untrusted results, and single point of failure. In this paper, we propose a blockchain-based anonymous attribute-based searchable encryption scheme for data sharing (BADS). First, attributes of the access policy are hidden, thus providing confidentiality to the set of attributes that satisfy the access policy. Then combining ABSE with blockchain have features of tamper-proof, integrity verification and non-repudiation. In particular, information such as secure index is stored in blockchain, while encrypted data is stored in a distributed system called the InterPlanetary File System (IPFS) to avoid single point of failure. Finally, BADS supports the matching algorithm that perform a fixed number of pairing operations before searching algorithm. We analysis security and evaluate performance to show the efficiency and practicability of BADS. IEEE

Keyword:

Attritude-based searchable encryption (ABSE) blockchain Blockchains Cloud computing Cryptography data sharing Encryption Indexes Keyword search matching policy hiding Servers

Community:

  • [ 1 ] [Zhang K.]School of Mathematics and Statistics, Shaanxi Normal University, Xi’an, China
  • [ 2 ] [Zhang Y.]School of Mathematics and Statistics, Shaanxi Normal University, Xi’an, China
  • [ 3 ] [Li Y.]School of Mathematics and Statistics, Shaanxi Normal University, Xi’an, China
  • [ 4 ] [Liu X.]School of Computer and Data Science, Fuzhou University, Fuzhou, China
  • [ 5 ] [Lu L.]School of Mathematics and Statistics, Shaanxi Normal University, Xi’an, China

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Source :

IEEE Internet of Things Journal

ISSN: 2327-4662

Year: 2023

Issue: 1

Volume: 11

Page: 1-1

8 . 2

JCR@2023

8 . 2 0 0

JCR@2023

ESI HC Threshold:32

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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