Shrew Distributed Denial-of-Service (DDoS) Attack in IoT Applications: A Survey

With the rise of IoT and cloud computing, DDoS attacks have become increasingly harmful. This paper presents a survey of techniques for detecting and preventing DDoS attacks, specifically focusing on Shrew DDoS or low-rate DDoS attacks. We explore the use of machine learning for DDoS detection and prevention and introduce a new potential technique that simplifies the process of detecting and preventing DDoS attacks originating from multiple infected machines, typically known as zombie machines. As a future direction, we discuss a new technique to simplify the detection and prevention of shrew DoS attacks originating from multiple infected machines, commonly known as botnets. The insights presented in this paper will be valuable for researchers and practitioners in cybersecurity.