Systematic Study on AI-Enabled Defense Against DDoS Attacks in IoT
Sandyarani Vadlamudi, A M Viswa Bharathy · 2025
People and machines are learning from the internet of things such as sensors, actuators, services and other things. Many facets of contemporary life have changed as a result of the Internet of Things (IoT), including home automation, industrial control systems, healthcare, and transportation. As the Internet of things applications are increasing attacks posing on these applications also increasing. One of the most dangerous threats when it comes to Internet of things is Distributed Denial of Service attack in which the attacks make services unavailable for the users. While the individuals responsible for DoS attacks, specifically DDoS attacks, do not intend to steal data, these attacks still pose a significant risk to networks. DDoS attacks aim to exhaust the resources of the targeted system, rendering it unable to provide its intended services. As a result, the system becomes dysfunctional. This study discussed about many machine learning and deep leaning algorithms for the DDoS attacks for several datasets that included IoT Network data.