| Title | Research on Automatic Generation and Analysis Technology of Network Attack Graph |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Hu, W., Zhang, L., Liu, X., Huang, Y., Zhang, M., Xing, L. |
| Conference Name | 2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS) |
| Keywords | Attack Graphs, attack target asset value, automatic generation, composability, dependence attack graph, edge authority attack graph, graph theory, Microelectronics, network attack graph, network security metrics, Network Security Reinforcement, network security reinforcement algorithm, network vulnerability index, optimisation, Optimization, Predictive Metrics, probability, Probability-based Network Vulnerability Measurement, pubcrawl, Resiliency, security, security of data |
| Abstract | In view of the problem that the overall security of the network is difficult to evaluate quantitatively, we propose the edge authority attack graph model, which aims to make up for the traditional dependence attack graph to describe the relationship between vulnerability behaviors. This paper proposed a network security metrics based on probability, and proposes a network vulnerability algorithm based on vulnerability exploit probability and attack target asset value. Finally, a network security reinforcement algorithm with network vulnerability index as the optimization target is proposed based on this metric algorithm. |
| DOI | 10.1109/BigDataSecurity-HPSC-IDS49724.2020.00033 |
| Citation Key | hu_research_2020 |
Research on Automatic Generation and Analysis Technology of Network Attack Graph