Name
Abstract | ||
|---|---|---|
Risk analysis is considered as an important process to identify the known and potential vulnerabilities and threats in the web services security. It is quite difficult for users to collect adequate events to estimate the full vulnerabilities and probability of threats in the Web, due to the rapid change of the malicious attacks and the new computer's vulnerabilities. In this paper, a fuzzy risk assessment model is developed in order to evaluate the risk of web services in a situation where complete information is not available. The proposed model extends Pseudo-Order Preference Model (POPM) to estimate the imprecise risk based on richness of information and to determine their ranking using a weighted additive rule. A case study of a number of web services is presented in order to test the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/s10586-007-0002-2 | Cluster Computing |
Keywords | Field | DocType |
Fuzzy outranking,Risk analysis,Web services security,Pseudo-order,POPM | Ranking,Risk analysis (business),Computer security,Computer science,Fuzzy logic,Risk assessment,Pseudo-order,Web service,Complete information,Vulnerability | Journal |
Volume | Issue | ISSN |
10 | 1 | 1386-7857 |
Citations | PageRank | References |
7 | 0.71 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ping Wang | 1 | 235 | 15.84 |
| Kuo-Ming Chao | 2 | 1123 | 130.82 |
| Chi-Chun Lo | 3 | 593 | 54.99 |
| Chun-Lung Huang | 4 | 118 | 10.05 |
| Muhammad Younas | 5 | 1031 | 124.26 |