A Resilience Recovery Method for Complex Traffic Network Security Based on Trend Forecasting
Beihang University · Beijing Automotive Group (China) · +1 more institution
Abstract
Due to the rapid development of information technology, a huge and complex traffic network has been established across various sectors including aviation, aerospace, vehicles, ships, electric power, and industry. However, because of the complexity and diversity of its structure, the complex traffic network is vulnerable to be attacked and faces serious security challenges. Therefore, this paper innovatively proposes a traffic network resilience recovery method based on resilience trend forecasting. In this paper, the risk value is introduced into the analysis of network fault propagation process, and the Susceptible, Infectious, Recovered, Dead‐Risk (SIRD‐R) fault propagation model is established. The…
Citation impact
- FWCI
- 32.70
- Percentile
- 100%
- References
- 28
Authors
7Topics & keywords
- Resilience (materials science)
- Computer science
- Network security
- Artificial intelligence
- Complex network
- Data mining
- Computer security
- World Wide Web