Merna Gamal1, Hala M. Abbas2, Nour Moustafa3,*, Elena Sitnikova3, Rowayda A. Sadek1
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1823-1837, 2021, DOI:10.32604/cmc.2021.012877
Abstract Intrusion Detection Systems (IDSs) have a great interest these days to discover complex attack events and protect the critical infrastructures of the Internet of Things (IoT) networks. Existing IDSs based on shallow and deep network architectures demand high computational resources and high volumes of data to establish an adaptive detection engine that discovers new families of attacks from the edge of IoT networks. However, attackers exploit network gateways at the edge using new attacking scenarios (i.e., zero-day attacks), such as ransomware and Distributed Denial of Service (DDoS) attacks. This paper proposes new IDS based on Few-Shot Deep Learning, named CNN-IDS,… More >