Name
Abstract | ||
|---|---|---|
In order to detect malicious web scripts automatically, many detection methods using static features and machine learning are proposed. However, the existing detection methods can only detect web scripts of specific programming languages. This paper proposes the unified text features and abstract syntax tree(AST) node sequence features algorithm(UTANSA) that exploits the text feature classificatio... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISCC53001.2021.9631400 | 2021 IEEE Symposium on Computers and Communications (ISCC) |
Keywords | DocType | ISBN |
Training,Computers,Computer languages,Machine learning algorithms,Computational modeling,Machine learning,Detectors | Conference | 978-1-6654-2744-9 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weiqing Huang | 1 | 3 | 10.21 |
| Chenggang Jia | 2 | 0 | 0.34 |
| Min Yu | 3 | 11 | 9.99 |
| Gang Li | 4 | 381 | 62.77 |
| Chao Liu | 5 | 0 | 0.34 |
| Jianguo Jiang | 6 | 0 | 1.01 |