The whole web world is concerned and constantly threatened by security intrusion. From the topmost corporate companies to the recently established start-ups, every company focuses on their network, system, and information security as it is the core of any company. Even a simple small security breach can cause a considerable loss to the company and compromises the CIA Triad (Confidentiality, Integrity, and Availability). Security concerns and hacking activities such as Distributed Denial of Service (DDoS) attacks are also experienced within home networks which could be saturated reaching a crashing point. This work focuses on using Artificial Intelligence (AI) and identifying suitable models to train, identify, and detect DDoS attacks. In addition, it aims to implement on smart home datasets and find the best model from those which performs with a high accuracy rate on the smart home dataset. The novelty of this project is identifying one best AI model among many of the existing models that works best on smart home datasets and in identifying and detecting DDoS attacks.