MICABAC: Multidimensional Industrial Control Attribute-Based Access Control Model
As the Industrial Control System (ICS) increasingly merges with the Internet, the security threats have been increasing from internal users and external hackers. These challenges are further intensified by the facts: industrial control devices and protocols, leading to the inadequacy of traditional access control models in tackling the intricacies of ICS. We identify attributes that are optimally aligned with the specific needs of the ICS environment and propose the Multidimensional Industrial Control Attribute-Based Access Control Model (MICABAC) as a customized solution. MICABAC model significantly improves access control security and is finer granularity by selecting and evaluating required attributes within various ICS. We have been validated in two real-world ICS environments: the Gas Pipe Network System (GPNS) and the Computer Numerical Control (CNC) machine tool. Experiments indicate that by integrating MICABAC into the existing system, the maximum delay for access requests is 63.83 ms. In terms of accuracy in defending against malicious attacks, the GPNS achieves 96.49% and the CNC reaches 94.86%. Finally, we discuss the advantages and limitations of MICABAC and explore potential directions for future research.
Authors
- Zhiwen Pan (ORCID: https://orcid.org/0000-0002-7266-7264)
- Shuaizong Si (ORCID: https://orcid.org/0000-0001-8805-1221)
- Limin Sun (ORCID: https://orcid.org/0000-0003-2745-7521)
- Fei Lv (ORCID: https://orcid.org/0000-0002-4226-7104)
- Yuqi Chen (ORCID: https://orcid.org/0000-0001-9769-1167)
- Hangyu Wang (ORCID: https://orcid.org/0009-0004-8234-2940)
- Degang Sun (ORCID: https://orcid.org/0009-0003-3418-8558)
Institutions
- ShanghaiTech University (CN)
- Institute of Information Engineering (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Published
- 2024-10-06
- DOI
- https://doi.org/10.1109/smc54092.2024.10830988
- Citations
- 2
- Primary Topic
- Access Control and Trust
- Type
- article
- Field-Weighted Citation Impact
- 2.26