Novel Method for Detecting DDoS Attacks to Make Robust IoT Systems
Sahil Koul, Rohit Wanchoo, Farah S. Choudhary · 2020
One particularly crippling attack on the traditional architecture of Internet or devices operated through Internet today is Denial of Service (DoS) attack. But the most notorious form of DoS attack is Distributed Denial of Service (DDoS), which adds the “many to one” dimension that makes these attacks more difficult to prevent. It compromises the availability of the target network or system by the distributed attacks which rely on recruiting a fleet of compromised hosts that unwittingly join forces to flood the victim server. This project focuses on proposing a novel method of detection of DDoS attacks by analyzing the network traffic history and combining the forces of this method with the AR time series model and chaos theory to form a faster and more stringent Network Anomaly Detection Algorithm (NADA), which can help IoT devices to be more robust.