![ITEA 4 page header azure circular](https://image.itea4.org/Pk0N6fU2T-zOkexSEltBIdpZnVM=/https://itea3.org/img/i/9486-1623848275.jpg)
ML based flooding attack detection
- Project
- 19045 STACK
- Type
- New system
- Description
This result is an ML-based flooding attack detection framework for Contiki OS and RPL networks.
- Contact
- YongUn choi, Sungmin Lee, JeongGil Ko
- jeonggil.ko@yonsei.ac.kr
- Research area(s)
- IoT security
- Technical features
Machine learning, Network attack detection
- Integration constraints
Use of RPL networks and Contiki/Contiki-NG
- Targeted customer(s)
Contiki OS users
- Conditions for reuse
None
- Confidentiality
- Public
- Publication date
- 08-12-2022
- Involved partners
- Yonsei University (KOR)