Name
Abstract | ||
|---|---|---|
Intrusion Detection Systems (IDSs) are an important defense tool against the sophisticated and ever-growing network attacks. These systems need to be evaluated against high quality datasets for correctly assessing their usefulness and comparing their performance. We present an Intrusion Detection Dataset Toolkit (ID2T) for the creation of labeled datasets containing user defined synthetic attacks. The architecture of the toolkit is provided for examination and the example of an injected attack, in real network traffic, is visualized and analyzed. We further discuss the ability of the toolkit of creating realistic synthetic attacks of high quality and low bias. |
Year | Venue | Field |
|---|---|---|
2015 | IEEE Conference on Communications and Network Security | Data mining,Architecture,Host-based intrusion detection system,Data visualization,Computer science,Computer security,Computer network,Intrusion detection system |
DocType | ISSN | Citations |
Conference | 2474-025X | 1 |
PageRank | References | Authors |
0.36 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos Garcia Cordero | 1 | 12 | 2.93 |
| Emmanouil Vasilomanolakis | 2 | 109 | 15.20 |
| Nikolay Milanov | 3 | 1 | 0.36 |
| Christian Koch | 4 | 31 | 4.95 |
| David Hausheer | 5 | 402 | 49.15 |
| Max Mühlhäuser | 6 | 1652 | 252.87 |