Networks heavily rely on middlebox to provide critical service functions, with the development of Software Defined Network (SDN) and Network Function Virtualization (NFV) technology, how to use the new technology to deploy middleboxs and guide flow through a specific sequence of middleboxs to complete the service function chain is still a problem to be solved. A construction method based on the optimal node utility maximization, namely NUM (Node Utility Maximization), was proposed for the service function chain construction problem, which took into account the deployment and steering of the virtual middleboxs in the meantime. Firstly, a service function chain collaborative construction mechanism was designed based on SDN+NFV technology. Secondly, the node selection model and the utility maximization model were introduced in this mechanism, according to the solution of middleware box deployment and traffic guidance problem. Finally, the model was solved by applying Tabu search-combined simulated annealing algorithm. The simulation results show that the proposed method NUM is superior to the traditional algorithm in terms of construction time, success rate and network congestion rate, and the utility of the nodes is improved by about 20% by using the proposed service function chain construction method.

In network sniffing attacks, attackers capture and analyze network communication data from network nodes or links, monitor network status and steal sensitive data such as usernames and passwords. In an ongoing attack, the attacker is usually in a silent state, traditional network protection methods such as firewalls, Intrusion Detection System (IDS), or Intrusion Prevention System (IPS) are difficult to detect and defend against it. A Dynamic Path Hopping (DPH) mechanism based on Software Defined Network (SDN) was proposed to solve this problem. In DPH, the paths of communication nodes were dynamically changed according to constraints of space and time, and the communication traffic was evenly distributed in multiple transmission paths, which increased the difficulty of obtaining complete data in the network sniffing attack. The experimental and performance simulation results show that under a certain network scale, DPH can effectively defend sniffer attacks without significantly reducing network transmission performance.