Traditional NSSA (network security situational awareness) systems have significant equipment limitations, poor data fusion capabilities, and a low level of analysis and evaluation, making them difficult to adapt to large-scale and complex network environments. This paper proposes the study of computer NSS (network security situation) prediction technology based on AR (association rules) mining to solve this problem. The support-confidence framework is improved by introducing an interest evaluation standard, and the value of AR is re-evaluated, based on a discussion of traditional concepts and algorithms related to AR mining. The MFP-interest algorithm proposed in this paper is a combination of alarm AR template and interest degree. The MFP-interest algorithm was put to the test. We discovered that the MFP-interest algorithm can effectively predict NSS and indicate its development trend when run in a real-world network environment. Most time points have a relative error range of less than 0.035.

The UAV carries communication equipment to lift off as an aerial base station, which has the characteristics of flexibility, rapid deployment, etc. Reducing the energy consumption of UAVs is a key issue that needs to be urgently addressed in the current UAV field to build green UAVs. The transmission service rate adaptivity of UAV devices provides an effective way to optimize UAV energy consumption and improve UAV energy efficiency, and a global and distributed UAV energy optimization routing strategy based on routing algorithm is proposed in this paper. The strategy starts from the perspective of UAV global routing and abstracts the UAV components that provide transmission services for data into a processing domain according to the service characteristics of UAVs. In the simulation experiments, the distributed heuristic algorithm for energy-optimized routing proposed in the paper is compared with the OSPF and GreenOSPF energy-efficient routing algorithms in the related literature, and the comparison results of the algorithms in terms of energy consumption and delay are presented.

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