The rapid evolution of Software-Defined Networking (SDN) has significantly transformed the landscape of network management and configuration, particularly within Information Technology (IT) and Operations Technology (OT) environments. Despite these advancements, SDN introduces new security and privacy challenges that require further investigation. This systematic literature review (SLR) analyzes existing research from 2016 to 2024, focusing on the key security and privacy concerns in SDN, particularly across the data plane, control plane, and application plane. We categorize and evaluate the main threats, including unauthorized access, denial of service (DoS) attacks, and advanced persistent threats (APTs), while also reviewing proposed solutions such as encryption techniques, intrusion detection systems (IDS), and blockchain-based security frameworks. Our analysis highlights trends in the evolution of security solutions, revealing a shift from conventional methods such as basic encryption to more adaptive approaches that incorporate AI, machine learning, and quantum-safe protocols. This review also identifies gaps in the current body of research, particularly in the areas of SDN integration with emerging technologies such as the Internet of Things (IoT), 5G, and edge computing. We conclude with recommendations for future research to address these challenges, including the need for standardized security protocols, advanced AI-driven threat detection, and secure, scalable frameworks for SDN in IT and OT networks.