## 1 Introduction  
The rapid development of sensing, activating, control, and networking technologies has enabled close fusion between various individuals that make up the physical world, such as machinery, electronic equipment, infrastructure, energy supply and consumption facilities, medical devices, and automobiles. Complex systems in systems technology, which fundamentally differentiate themselves from existing individual electronic devices by collecting and analyzing necessary information from physical objects through various sensors and sharing processed information with various controllers and actuators, have been proposed and developed. In this way, a cognitive control system in which cyber world information processing functions and the physical world respond closely to each other and cooperate is called cyber-Physical Systems (CPSs). Cyber-Physical systems are expected to be applied to most information processing and control computing fields, contributing dramatically to the improvement of efficiency, safety, and security. In particular, on the basis of intelligent cyber information collection and optimal control technologies, it is expected to be applied to various fields such as city intelligent traffic control, building group energy-consumption analysis and optimal control, and smart space service. The Internet of Things (IoT), combined with the main social infrastructure of real life, reveals dangers that exist in cyberspace, such as the theft of personal information by hacking home appliances and spreading malware infections in the real world. However, as the IoT combines major social infrastructures with our real-life things, the number of security threats is skyrocketing. For example, the dangers in cyberspace, such as theft of personal information by hacking home appliances and malware infections, are appearing. It is also possible to hack passwords to open the doors of smart cars, illegally exercise authority that only the owner of the smart car has, force the smart car itself to move, or steal it. Not only that, it is also possible to track the locations of smart cars and remotely attack their hardware to prevent them from working properly [1; 2; 3; 4]. Big data environments are combined with the IoT infrastructure and cloud environments to provide platforms and services, but security solutions that remain in individual units are missing consistent security policies, slowing down decision-making, etc., and are becoming a problem. Therefore, new customized security services are needed in the various network environments (e.g., the IoT, the CPSs, the cloud, big data, etc.). New combined environmental urban transport systems will continue to be important for safety and will be combined with new IoT infrastructure for technologies that detect and avoid risks. In addition, the importance of safety will not change in future urban transportation systems, and the demand for technologies to detect and avoid the risks of movement will increase. In transportation networks, a huge amount of data is exchanged, such as the number of automobiles, the movements of millions of people, and the transfer of personal information, which are all bound together by external environmental information. Modern mobile communication systems are mechanisms that process information that is collected on a central server and sent to each mobile unit. At present, the time available for judgment is insufficient because of problems such as network latency. In other words, moving a large amount of data requires individual real-time processing. In addition, it is possible to obtain necessary information, such as nearby accident information and traffic jam information, by exchanging information on geographically close movement or movement in previous similar situations. However, it is very difficult to collect information from many mobile units on a central server and make it searchable. In such a case, it is necessary to extract only important data, reduce the total storage, and transfer only important information.