Name
Abstract | ||
|---|---|---|
We present a novel approach to detect misuse within an information retrieval system by gathering and maintaining knowledge of the behavior of the user rather than anticipating attacks by unknown assailants. Our approach is based on building and maintaining a profile of the behavior of the system user through tracking, or monitoring of user activity within the information retrieval system. Any new activity of the user is compared to the user profile to detect a potential misuse for the authorized user. We propose four different methods to detect misuse in information retrieval systems. Our experimental results on $2$ GB collection favorably demonstrate the validity of our approach. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1145/956863.956901 | CIKM |
Keywords | Field | DocType |
novel approach,information retrieval system,user profile,authorized user,misuse detection,different method,user activity,system user,gb collection,potential misuse,new activity,information retrieval,clustering | Data mining,Cognitive models of information retrieval,Relevance feedback,Human–computer information retrieval,User profile,Information retrieval,Computer science,Relevance (information retrieval),Cluster analysis,Misuse detection | Conference |
ISBN | Citations | PageRank |
1-58113-723-0 | 17 | 1.52 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rebecca Cathey | 1 | 26 | 5.08 |
| Ling Ma | 2 | 50 | 5.36 |
| Nazli Goharian | 3 | 460 | 49.93 |
| David Grossman | 4 | 525 | 34.73 |