Document Type
Article
Publication Date
2015
College/Unit
Statler College of Engineering and Mining Resources
Department/Program/Center
Lane Department of Computer Science and Electrical Engineering
Abstract
In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised devices depend on the incremental response time in the attestation process, which are sensitive to data transmission delay and lead to high computation and network overhead. To address the issue, in this paper, we propose a low-cost remote memory attestation scheme (LRMA), which can efficiently and accurately detect compromised smart meters considering real-time network delay and achieve low computation and network overhead. In LRMA, the impact of real-time network delay on detecting compromised nodes can be eliminated via investigating the time differences reported from relay nodes. Furthermore, the attestation frequency in LRMA is dynamically adjusted with the compromised probability of each node, and then, the total number of attestations could be reduced while low computation and network overhead can be achieved. Through a combination of extensive theoretical analysis and evaluations, our data demonstrate that our proposed scheme can achieve better detection capacity and lower computation and network overhead in comparison to existing schemes.
Digital Commons Citation
Yang, Xinyu; He, Xiaofei; Yu, Wei; Lin, Jie; Li, Rui; Yang, Qingyu; and Song, Houbing, "Towards a Low-Cost Remote Memory Attestation for the Smart Grid" (2015). Faculty & Staff Scholarship. 2169.
https://researchrepository.wvu.edu/faculty_publications/2169
Source Citation
Yang, X., He, X., Yu, W., Lin, J., Li, R., Yang, Q., & Song, H. (2015). Towards a Low-Cost Remote Memory Attestation for the Smart Grid. Sensors, 15(8), 20799–20824. https://doi.org/10.3390/s150820799
Comments
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited