Dynamic Evaluation Method Of The Software Trustworthiness Based On Scene Information

In the information era,software applications play an increasingly important role in the national economy.The software is not only applied to aerospace,energy and telecommunications industries,but also covers many fields of daily life.The demand and application of software are more and more,at the same time,people's tolerance to software quality is getting lower and lower,which also leads to more and more trustworthiness problems of software.In addition,as the complexity of the software system increases,it becomes more and more fragile,which may lead to the operation of the software deviating from the desired trajectory and causing failure.Some of these failures are obvious,but some are invisible.Although the software seems to be running,it can actually suffer drawbacks such as incorrect results,incorrect data storage,or some security constraints being destroyed[1].As a result,how to evaluate the trustworthiness of the software behavior is a highly desirable research topic.This thesis mainly studies the worthiness of software behavior.The main tasks completed are as follows:(1)Software trustworthiness evaluation model based on behavior trajectory matrixThe existing software trustworthiness evaluation methods are generally dependent on human factors,such as experts' experience or users' satisfaction.To ensure the objectivity of the trustworthiness evaluation of software behavior,in this paper,a software trustworthiness evaluation model based on behavior trajectory matrix was proposed.A number of checkpoints were set up in the trajectory of software behavior,and binary code was introduced to express software behavior trajectory tree.On this basis,the scene information of checkpoints was obtained,which was represented as a behavior trajectory matrix,and used to represent the behavior trajectory,and then the behavior trajectory matrix was transformed into a gray image.The Deep Residual Network(ResNet)and Cosine Similarity Algorithm(CSA)were used to evaluate the trustworthiness of current software behavior.(2)Software behavior trust forecast model based on check point scene informationTo predict the trustworthiness of the future operation trend of software and reduce unnecessary losses,a software behavior trust forecast model on checkpoint scene information which is called CBSI-TM was presented.The model set up a number of checkpoints in the software running track,and introduced the time increment of adjacent checkpoints,and the change of CPU utilization rate to define the scene information,and reflected the relationship between adjacent checkpoints scene information.Then the RBF neural network classifier evaluated the status of the current checkpoint to judge the trustworthiness of the software,and the semi weighted Markov model predicted the situation of the next checkpoint to evaluate the trustworthiness of future running trend of the software.