NBC-MAIDS: Naïve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks

Abstract

Internet of Things (IoT) makes physical objects and devices interact with each other through wireless technologies. IoT is expected to deliver a significant role in our lives in near future. However, at the current stage, IoT is vulnerable to various kinds of security threats just like other wired and wireless networks. Our work mainly focuses on protecting an IoT infrastructure from distributed denial-of-service attacks generated by the intruders. We present a new approach of using Naïve Bayes classification algorithm applied in intrusion detection systems (IDSs). IDSs are deployed in the form of multi-agents throughout the network to sense the misbehaving or irregular traffic and actions of nodes. In the paper, we also discuss the fundamental concepts related to our work and recent research done in similar area.