AACS: A Secure Attribute Based Data Access Control for Cloud-Aided Internet of Vehicles Using SGX

Internet of Vehicles (IoV) is a promising technology to equip transportation management systems with digitalized ability. The deployed IoV devices allow traffic participants to generate and analyze the traffic information such as driving status and road condition. They can further share the collected traffic data through the centralized cloud service to improve road operation efficiency, safety and reduce economic losses. Storing sensitive traffic data in an untrusted cloud server, however, raises the requirement of data access control to protect valuable business issues. Unfortunately, using pure cryptographic access control schemes for traffic data faces several limitations. In this paper, we first develop a pure cryptographic construction to enforce attribute-based access control (ABAC) model in untrusted cloud for IoV system based on ciphertext policy-attribute based encryption (CP-ABE) and explore three limitations of it. By studying ABAC in the context of CP-ABE, we can effectively lower-bound the costs that would be incurred when using more advanced and more expensive predicate encryption schemes. We then propose a new attribute based access control system (AACS) for cloud-aided IoV system to overcome the barriers of CP-ABE by using trusted hardware (Intel Software Guard Extensions (SGX)). AACS uses a secure data division framework to achieve a small Trusted Computing Base (TCB) and integrates SGX with several cryptographic protocols as well as optimization techniques. We comprehensively evaluate AACS to show the design advantages of it.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2024-08-23
DOI
https://doi.org/10.1109/tvt.2024.3398062
Citations
5
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
1.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AACS: A Secure Attribute Based Data Access Control for Cloud-Aided Internet of Vehicles Using SGX

Saiyu Qi, Yong Qi, Kashif Saleem, Xu Yang et al.
5 citations
IEEE Transactions on Vehicular Technology
Cryptography and Data Security
1.74
article

AACS: A Secure Attribute Based Data Access Control for Cloud-Aided Internet of Vehicles Using SGX

Saiyu Qi, Yong Qi, Kashif Saleem, Xu Yang, Wei Wei, Jun Gu, Wenjia Zhao
article en
5 citations

Abstract

Internet of Vehicles (IoV) is a promising technology to equip transportation management systems with digitalized ability. The deployed IoV devices allow traffic participants to generate and analyze the traffic information such as driving status and road condition. They can further share the collected traffic data through the centralized cloud service to improve road operation efficiency, safety and reduce economic losses. Storing sensitive traffic data in an untrusted cloud server, however, raises the requirement of data access control to protect valuable business issues. Unfortunately, using pure cryptographic access control schemes for traffic data faces several limitations. In this paper, we first develop a pure cryptographic construction to enforce attribute-based access control (ABAC) model in untrusted cloud for IoV system based on ciphertext policy-attribute based encryption (CP-ABE) and explore three limitations of it. By studying ABAC in the context of CP-ABE, we can effectively lower-bound the costs that would be incurred when using more advanced and more expensive predicate encryption schemes. We then propose a new attribute based access control system (AACS) for cloud-aided IoV system to overcome the barriers of CP-ABE by using trusted hardware (Intel Software Guard Extensions (SGX)). AACS uses a secure data division framework to achieve a small Trusted Computing Base (TCB) and integrates SGX with several cryptographic protocols as well as optimization techniques. We comprehensively evaluate AACS to show the design advantages of it.

IEEE Transactions on Vehicular TechnologyVol. 74(2)
King Saud University (SA), Xi'an Jiaotong University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Cryptography and Data Security
1.74
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.