Name
Abstract | ||
|---|---|---|
Security in telemedicine systems might be considered a par- ticularly sensitive subject due to the type of confidential information generally handled and the responsibilities consequently derived. In this work we focus on detecting attempts of gaining unauthorised access to a telemedicine web application. We introduce a new Text Mining mod- ule that by using Text Categorisation of the web application server log entries is capable of learning the characteristics of both normal and ma- licious user behaviour. As a result, the detection of misuse in the web application is achieved without the need of explicit programming hence improving the system maintainability. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11589990_131 | Australian Conference on Artificial Intelligence |
Keywords | Field | DocType |
web-based telemedicine system,malicious user behaviour,text mining,text categorisation,system maintainability,web application server log,confidential information,web application,telemedicine system,intrusion detection,explicit programming,new text mining module,telemedicine web application,web application server,information retrieval,artificial intelligence,data mining,maintainability,categorization,machine learning,data privacy,world wide web,internet,intrusion detection systems,computer security | World Wide Web,Computer science,Computer security,Web modeling,Web application security,Web application,Information privacy,Web service,Intrusion detection system,Application server,The Internet | Conference |
Volume | ISSN | ISBN |
3809 | 0302-9743 | 3-540-30462-2 |
Citations | PageRank | References |
1 | 0.35 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. J. García Adeva | 1 | 23 | 2.31 |
| J. M. Pikatza | 2 | 3 | 0.78 |
| S. Flórez | 3 | 1 | 0.35 |
| F. J. Sobrado | 4 | 1 | 0.35 |