Biblio

Cities are becoming increasingly smart as the Internet of Things (IoT) proliferates. With IoT devices interconnected, smart cities can offer novel and ubiquitous services as well as automate many of our daily lives (e.g., smart health, smart home). The abundance in the number of IoT devices leads to divergent types of security threats as well. One of such important attacks is the Distributed Denial of Service attack(DDoS). DDoS attacks have become increasingly common in the internet of things because of the rapid growth of insecure devices. These attacks slow down legitimate network requests. Although DDoS attacks were first reported in 1996, the sophistication of these attacks has increased significantly. In mid-August 2020, a 2 Terabytes per second(TBps) attack targeting critical infrastructure, such as finance, was reported. In the next two years, it is predicted that this number will double to 15 million attacks. Blockchain technology, whose development dates back to the advent of the internet, has become one of the most important advancements to come along since that time. Several applications can use this technology to secure exchanges. Using blockchain to mitigate DDoS attacks is discussed in this survey paper in diverse domains to date. Its purpose is to expose the strengths, weaknesses, and limitations of the different approaches to DDoS mitigation. As a research and development platform for DDoS mitigation, this paper will act as a central hub for a more comprehensive understanding of these approaches.

Internet of Things (IoT) is transforming the way we live today, improving the quality of living standard and growing the world economy by having smart devices around us making decisions and performing our daily tasks and chores. However, securing the IoT system from malicious attacks is a very challenging task. Some of the most common malicious attacks are Denial of service (DoS), and Distributed Denial of service (DDoS) attacks, which have been causing major security threats to all networks and specifically to limited resource IoT devices. As security will always be a primary factor for enabling most IoT applications, developing a comprehensive detection method that effectively defends against DDoS attacks and can provide 100% detection for DDoS attacks in IoT is a primary goal for the future of IoT. The development of such a method requires a deep understanding of the methods that have been used thus far in the detection of DDoS attacks in the IoT environment. In our survey, we try to emphasize some of the most recent Machine Learning (ML) approaches developed for the detection of DDoS attacks in IoT networks along with their advantage and disadvantages. Comparison between the performances of selected approaches is also provided.