Project 304 (1st year)
Intrusion Detection and Prevention
| iCAST project 304, aims to support intrusion detection and prevention (IDS/IPS), whereby applying machine learning mechanism and artificial intelligent technique to build the kernel detected techniques. By doing so, we can accomplish two significant goals: one is alert correlation related issues, such as multi-steps attack, attack intention analysis, adaptive analysis; another is alert correlation benchmark construction for validation. This project is currently in early deployment stages. If you have an account, or for further information please feel free to mail us. |
Member List
| Country | Organization | Full Name | Title | |
|---|---|---|---|---|
Taiwan |
TWISC |
Lee, Hahn-Ming |
PI |
|
Taiwan |
TWISC |
Lee, Yuh-Jye |
Co-PI |
|
Taiwan |
TWISC |
Ho, Cheng-Seen |
Co-PI |
|
Taiwan |
TWISC |
Pao, Hsing-Kuo |
Investigator |
|
Taiwan |
TWISC |
Wu, Yi-Leh |
Investigator |
|
Taiwan |
TWISC |
Mao, Ching-Hao |
Assistant |
|
Taiwan |
TWISC |
Lin, Heng-Sheng |
Assistant |
|
Taiwan |
TWISC |
Chien, Sheng-Hui |
Assistant |
|
US |
CMU |
Dawn Song |
Professor |
|
US |
CMU |
Tsuhan Chen |
Professor |
Required Documents (1st year)
Self-Assessment Presentation File (Internal Review Meeting)
Midterm Report (External Review Meeting)
Final Report (External Review Meeting)