Name
Abstract | ||
|---|---|---|
Traditional security solutions for web services or service composition are access control based models. In this paper, a new approach, sequence analysis based anomaly detection (SABAD) model for service composition is proposed to deal with the insecurity factors. SABAD model includes two parts, one is to mine abnormal service sequence patterns by extracting and analyzing service sequences, the other is to match sequence patterns and find anomaly. In order to integrate with access control policies, the abnormal sequence patterns are made up of static patterns given by system administrator beforehand and dynamic patterns mined by related algorithm. For certain incoming request, a service sequence is extracted firstly, and then matched with the abnormal sequence patterns to determine it safe or unsafe. The experiment results show that SABAD model can not only provide traditional access control but also assure timely anomaly detection and improve the true positive rate of detecting anomalies. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CSSE.2008.262 | CSSE (3) |
Keywords | Field | DocType |
data mining,authorisation,anomaly detection,sequence analysis,pattern matching,web services,web service,access control,security | Data mining,Anomaly detection,Computer science,Service composition,Artificial intelligence,Web service composition,System administrator,Access control,Web service,Pattern matching,Database,Machine learning,Sequence analysis | Conference |
Volume | Issue | Citations |
3 | null | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cairong Yan | 1 | 18 | 4.06 |
| Zhidong Qin | 2 | 0 | 1.01 |
| Youqun Shi | 3 | 11 | 5.04 |