Software-defined networking (SDN) is an emerging network architecture that considerably improves the performance of traditional networks through network management, programmability, dynamism, and scalability. SDN architecture separates the control plane and the data plane. It uses a controller to collect the topology information of the network elements via the OpenFlow Protocol. These new features of the SDN architecture can cause serious security challenges. For example, an attacker can exploit the centralized controller as a single point of failure and generate a distributed denial-of-service (DDoS) attack on the SDN controller. One of the most effective solutions is usually called an intrusion detection system (IDS) to ensure a high level of network security. This survey reviewed various security challenges and recent works on statistical-based IDS and machine learning (ML) methods that leverage SDN to implement NIDS.