The Fifth Generation of Communication Networks (5G) envisions a broader range of services compared to previous generations, supporting an increased number of use cases and applications. The broader application domain leads to increase in consumer use and, in turn, increased hacker activity. Due to this chain of events, strong and efficient security measures are required to create a secure and trusted environment for users. In this paper, we provide an objective overview of 5G security issues and the existing and newly proposed technologies designed to secure the 5G environment. We categorize security technologies using Open Systems Interconnection (OSI) layers and, for each layer, we discuss vulnerabilities, threats, security solutions, challenges, gaps and open research issues. While we discuss all seven OSI layers, the most interesting findings are in layer one, the physical layer. In fact, compared to other layers, the physical layer between the base stations and users’ device presents increased opportunities for attacks such as eavesdropping and data fabrication. However, no single OSI layer can stand on its own to provide proper security. All layers in the 5G must work together, providing their own unique technology in an effort to ensure security and integrity for 5G data.

The proliferation of IoT devices and integration of machine learning technologies paved the path towards automation in various sectors such as manufacturing, communication, automobiles, agricultural, health etc. guided by Artificial intelligence (AI). As space exploration is transitioning from a mere idea to a tangible reality, the integration of AI-powered IoT will be an essential aspect of space colonies, where self-governing systems will be the norm. These IoT networks will have a broad range of coverage that will extend to the farthest limits with the aid of low orbit satellite integration. However, the widespread adoption of these IoT technologies is highly contingent on ensuring that data is protected from malevolent intrusions. Therefore, in this paper we have proposed a federated learning based distributed approach in an SDN environment to thwart data breach that can plague satellite-IoT framework with respect to space communication. Additionally, as part of the implementation of the framework, we have devised an SDN backbone equipped with a traffic regulator to prevent malicious traffic flows in the network. Our system correctly classifies malicious traffic, blocks flood sources and ensures safe data transmission between IoT devices. The implemented OpenMined-based federated learning method is promising with an accuracy rate of 79.47% in detecting attacks. Our future work will be focused on improving the accuracy of the federating learning-based approach and in conducting differential privacy-based approaches to demonstrate the privacy related advantages of the proposed framework.