A FeedForward–Convolutional Neural Network to detect low-rate DoS in IoT

• Main Authors: Ilango, Harun Surej, Ma, Maode, Su, Rong
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• 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; CIC DoS 2017; Anomaly Detection; Network Security
• Online Access: https://hdl.handle.net/10356/167102
• Institution: Nanyang Technological University

The lack of standardization and the heterogeneous nature of the Internet of Things (IoT) has exacerbated the issue of security and privacy. In literature, to improve security at the network layer of the IoT architecture, the possibility of using Software-Defined Networking (SDN) was explored. SDN is...