Genetic Algorithm Service Vulnerability Mining Technology of Android System

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XiaoYan Guo
YanFeng Sun


The inland ships energy efficiency is significantly influenced by navigational environment, including speed and direction of wind and water depth. In order to solve the problem of low efficiency of conventional fuzzy test mining, a research method of Android system Service Vulnerability mining technology based on Genetic Algorithm (GA) is proposed. An efficient genetic selection operator model based on probability ranking and combination is also presented to improve the sample coverage and fuzzy test efficiency. Through the framework testing on different systems of mobile phones, multiple system service vulnerabilities are excavated. The execution results guide the generation of test cases, which reduces the proportion of invalid parameters in the test process to improve the efficiency of fuzzy testing. It is observe that the fuzzy test based on GA is much better than the conventional fuzzy test method in the vulnerability mining of system services, and has certain effectiveness and superiority. In addition, after using the two-point crossover algorithm to recombine the gene strings of two individuals, the phenotype of the newly generated individual gene string may become meaningless. It is observed that the selection algorithm factor has a very low p-value, while the ANOVA test confirms at least two groups that have statistically-significant difference.

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Special Issue - Intelligent Cloud Technologies