Name
Abstract | ||
|---|---|---|
Darknet monitoring provides us an effective way to countermeasure cyber attacks that pose a significant threat to network security and management. This paper aims to characterize the behavior of long term cyber attacks by mining the darknet traffic data collected by the nicter project. Machine learning techniques such as clustering, classification, function regression are applied to the study with promising results reported. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-34500-5_73 | ICONIP (5) |
Keywords | DocType | Volume |
darknet monitoring,behavior analysis,nicter project,function regression,long-term cyber attack,network security,cyber attack,long term cyber attack,significant threat,promising result,darknet traffic data | Conference | 7667 |
ISSN | Citations | PageRank |
0302-9743 | 5 | 0.61 |
References | Authors | |
12 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Ban | 1 | 102 | 25.58 |
| Lei Zhu | 2 | 15 | 1.14 |
| Junpei Shimamura | 3 | 5 | 0.61 |
| Shaoning Pang | 4 | 711 | 52.69 |
| Daisuke Inoue | 5 | 67 | 17.51 |
| Koji Nakao | 6 | 194 | 19.09 |