| Title | A cross-layer attack path detection method for smart grid dynamics |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Wang, Binbin, Wu, Yi, Guo, Naiwang, Zhang, Lei, Liu, Chang |
| Conference Name | 2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) |
| Keywords | bidirectional detection, composability, compositionality, Computers, Cross layer design, Cross Layer Security, cross-layer attack, forward-backward, Physical layer, Power system dynamics, Predictive models, pubcrawl, Real-time Systems, resilience, Resiliency, Smart grid, Smart grids |
| Abstract | With the intelligent development of power system, due to the double-layer structure of smart grid and the characteristics of failure propagation across layers, the attack path also changes significantly: from single-layer to multi-layer and from static to dynamic. In response to the shortcomings of the single-layer attack path of traditional attack path identification methods, this paper proposes the idea of cross-layer attack, which integrates the threat propagation mechanism of the information layer and the failure propagation mechanism of the physical layer to establish a forward-backward bi-directional detection model. The model is mainly used to predict possible cross-layer attack paths and evaluate their path generation probabilities to provide theoretical guidance and technical support for defenders. The experimental results show that the method proposed in this paper can well identify the dynamic cross-layer attacks in the smart grid. |
| DOI | 10.1109/AEMCSE55572.2022.00036 |
| Citation Key | wang_cross-layer_2022 |
A cross-layer attack path detection method for smart grid dynamics