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
Email: 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)