Low rate DoS attack detection in IoT - SDN using deep learning

• Main Authors: Ilango, Harun Surej, Ma, Maode, Su, Rong
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2023
• Subjects: Engineering; Engineering::Electrical and electronic engineering; Engineering::Electrical and electronic engineering::Wireless communication systems; Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Internet of Things; Software Defined Networking; Deep Learning; Low-Rate DoS Attacks; Network Security; CIC DoS 2017; CIC IDS 2017
• Online Access: https://hdl.handle.net/10356/167111
• Institution: Nanyang Technological University

The lack of standardization and the heterogeneous nature of IoT, exacerbated the issue of security and privacy. In recent literature, to improve security at the network level, the possibility of using SDN for IoT networks was explored. An LR DoS attack is an insidious DoS attack that hinders the ava...