DDoS attacks in Industrial IoT: A survey

As the IoT expands its influence, its effect is becoming macroscopic and pervasive. One of the most discernible effects is in the industries where it is known as Industrial IoT (IIoT). IIoT provides automated, comprehensive, regressive and easy-to-use methods to look over its components. Along with the benefits, it also brings concerns that spawn from the IoT itself. Moreover, the challenges in the industries also add up because they have their own set of requirements and procedures to perform. Among those challenges, one of the prominent is DDoS attacks. So, through this paper, the DDoS attacks in IIoT is studied. This paper has culminated the work done in the domain involving IoT and IIoT. With this different forms of attacks involved in DDoS, the tools involved in generating the attacks and the overall traffic generators is also discussed. To elucidate, IIoT architecture and various layers involved in communication is discussed to correlate the threat of DDoS attacks in IIoT. Further, the studies made in various categories such as machine learning, deep learning, federated learning and transfer learning is elaborated. Finally, the challenges present in IIoT and the security requirements needed to overcome challenges in IIoT is explained.