Traceable Access Control Encryption With Parallel Multiple Sanitizers

Access control encryption (ACE) is an innovative cryptographic primitive that realizes fine-grained read/write control of data and protects data privacy and security while facilitating the effective flow of information. However, existing ACE schemes face several limitations: 1) Inability to adequately mitigate the risks of a single point of failure in the sanitizer. 2) Lack of an effective accountability mechanism for disputes arising during the sanitization process. To solve these problems, this paper proposes the notion of traceable access control encryption with parallel multiple sanitizers for the first time and designs a specific structure of traceable parallel ACE to prevent the single point of failure, effectively deter abnormal sanitizer behaviors, and optimize system performance. Additionally, computationally intensive operations in the encryption and decryption processes are outsourced to third-party servers, resulting in a significant reduction of computational overhead. Furthermore, theoretical analysis and experimental simulations validate the effectiveness of the proposed scheme. Comprehensive security analysis demonstrates its no-read security under the decisional q-parallel Bilinear Diffie-Hellman Exponent (BDHE) assumption and its no-write security under the Discrete Logarithm (DL) assumption, ensuring its reliability in practical applications.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Information Forensics and Security
Published
2025-01-01
DOI
https://doi.org/10.1109/tifs.2025.3611076
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Traceable Access Control Encryption With Parallel Multiple Sanitizers

Wei Luo, Chengzhe Lai, Qinghe Duan
IEEE Transactions on Information Forensics and Security
Cryptography and Data Security
article

Traceable Access Control Encryption With Parallel Multiple Sanitizers

Wei Luo, Chengzhe Lai, Qinghe Duan
article en

Abstract

Access control encryption (ACE) is an innovative cryptographic primitive that realizes fine-grained read/write control of data and protects data privacy and security while facilitating the effective flow of information. However, existing ACE schemes face several limitations: 1) Inability to adequately mitigate the risks of a single point of failure in the sanitizer. 2) Lack of an effective accountability mechanism for disputes arising during the sanitization process. To solve these problems, this paper proposes the notion of traceable access control encryption with parallel multiple sanitizers for the first time and designs a specific structure of traceable parallel ACE to prevent the single point of failure, effectively deter abnormal sanitizer behaviors, and optimize system performance. Additionally, computationally intensive operations in the encryption and decryption processes are outsourced to third-party servers, resulting in a significant reduction of computational overhead. Furthermore, theoretical analysis and experimental simulations validate the effectiveness of the proposed scheme. Comprehensive security analysis demonstrates its no-read security under the decisional q-parallel Bilinear Diffie-Hellman Exponent (BDHE) assumption and its no-write security under the Discrete Logarithm (DL) assumption, ensuring its reliability in practical applications.

IEEE Transactions on Information Forensics and SecurityVol. 20
Xi’an University of Posts and Telecommunications (CN)
Openalex Percentile: Top 87%
Cryptography and Data Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.