Information Security Theory Is Used To Construct AMS Intelligent Monitoring And Early Warning System

China is the country with the highest altitude and the largest population.With the rapid economic and social development of the plateau region,the number of people who have rushed to the plateau is increasing day by day,and the Acute Mountain Sickness(AMS)caused by hypoxia has become a major threat to the health of those who have rushed to the plateau.There are corresponding criteria for the clinical diagnosis of AMS,namely Lake Louise international diagnostic criteria for acute altitude sickness and the domestic principles for the diagnosis and management of acute mountain sickness.Both of these criteria are based on subjective symptoms for scoring,while there are few studies on the use of objective indicators to build mathematical models for the diagnosis of AMS.In addition,the research on real-time monitoring and early warning of AMS using information technology is still not mature.In view of the above problems,this paper constructs AMS intelligent monitoring and early warning system based on information security theory,which provides a solution for rapid screening and prevention of acute mountain sickness.The main research contents of this paper are as follows:(1)In order to realize the rapid screening and prevention of AMS,the AMS intelligent monitoring and early warning system is constructed.This system uses the meta-fog redirection architecture based on fog computing to reclassify and directional store data,effectively integrates cloud computing and fog computing to transmit data safely to different cloud databases through the fog aggregation architecture,and uses the built early warning model to diagnose and warn AMS.This not only improves the security of AMS intelligent information service,but also effectively improves the system efficiency.(2)In order to ensure the safe transmission of information,an aggregation sign-secret scheme based on data collection scenario is proposed to support member joining and cancellation.This scheme can compress the signature of any number of members into one signature and encrypt it,and support the addition and retract of any member.Therefore,it can effectively solve the signature bloat problem existing in AMS real-time monitoring system and enhance the data confidentiality.Under the random prediction model,it is proved that the scheme has such security features as nonforgery,confidentiality and non-repudiation,and can provide security authentication for the collected data with low computing cost,which effectively realizes the confidentiality and security of the data in the transmission process.(3)In order to realize real-time monitoring and early warning of AMS,this paper constructs an AMS early warning function model based on the project response theory and binomial logistics regression equation.Maximum likelihood estimation method was used for model analysis.Through data simulation,it is verified that the model has high goodness of fit and accuracy of prediction.