Name
Abstract | ||
|---|---|---|
To protect our networks against malicious intrusions, we need to evaluate these networks security. Previous works on attack graphs have provided meaningful conclusions on security measurement. However, large attack graphs are still hard to be understood vividly, and few suggestions have been proposed to prevent inside malicious attackers from attacking networks. To address these problems, we propose a novel approach to evaluate network security based on adjacency matrixes, which are constructed from existing attack graphs. With our model, we use gray scale images to show overall security vividly, and get quantitative evaluation scores. Moreover, we create a prioritized list of potential threatening hosts, which can help network administrators to harden network step by step. Analysis on computation cost shows that the upper bound computation cost of our measurement methodology is O(N3), which could be completed in real time. We also give an example to show how to put our methods in practice. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICC.2010.5502655 | ICC |
Keywords | Field | DocType |
network security,adjacency matrixes-based model,attack graphs,matrix algebra,adjacency matrixes,gray scale images,measurement methodology,computational complexity,security measurement,network security analysis,graph theory,telecommunication security,malicious intrusions,educational technology,computer science education,measurement,adjacency matrix,computer science,computer security,security,upper bound,computational modeling,real time | Adjacency list,Graph theory,Computer security,Matrix (mathematics),Computer science,Upper and lower bounds,Network security,Computer network,Theoretical computer science,Grayscale,Computation,Computational complexity theory | Conference |
Volume | Issue | ISSN |
null | null | 1550-3607 |
ISBN | Citations | PageRank |
978-1-4244-6402-9 | 1 | 0.39 |
References | Authors | |
11 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anmin Xie | 1 | 1 | 0.73 |
| Cong Tang | 2 | 20 | 7.18 |
| Nike Gui | 3 | 4 | 2.13 |
| Zhuhua Cai | 4 | 90 | 7.48 |
| Jianbin Hu | 5 | 179 | 22.43 |
| Zhong Chen | 6 | 503 | 58.35 |