Cloud computing is a critical aspect of today’s technology. It’s an over the internet way of accessing and using large amounts of computing services. Users pay less than if they were managing their own computer infrastructure. This lets users store a large amount of data. Many IT companies and resources are expected to focus on cloud computing moving forward. Cloud computing has been facing several security risks through its continuous development. One of the biggest is Distributed Denial of Service attacks. These attacks aim to shut down and prevent regular users from accessing the cloud computing service. These attacks are detrimental since the types of users who use cloud computing range widely and when the servers are unavailable multiple users lose access to the computer services offered by their cloud. This literature reviews goal is to bring forward the results of various research focused on current ML and DL based DDoS detection. This paper aims to analyze and compare the works viewed and find the algorithms that preformed the best for each of the evaluation criteria. Those being accuracy, recall, and precision. After analyzing the current state of Cloud computing’s ML and DL based DDoS detection we will move onto future work. This future work includes testing and verifying the efficiency of the best algorithms in each evaluation criteria category.