模糊测试变异算子调度优化模型

Fuzzy Tester Mutation Operator Scheduling Optimization Algorithm

模糊测试技术是一种使用不同变异算子生成测试用例对程序进行漏洞检测的技术.当前对模糊测试技术的研究集中在变异算子的设计与程序分析两个方面,对多种变异算子之间的协同调度还没有进行深入研究.文章首先对模糊测试中通用的15个变异算子进行研究,分析不同变异算子在不同类型程序上的变异效率.文章以探索与利用模型为基础,结合变异算子变异效率变化的规律,设计了变异算子调度优化模型EE-POS,以提高模糊测试技术的漏洞挖掘效率.文章在原型系统EE-POS-AFL上实现了EE-POS变异算子调度优化模型,通过与AFL的对比实验表明EE-POS-AFL路径探索效率提高63%,漏洞检测效率提高153%.

Fuzzing technology is a technology that uses different mutation operators to generate test cases to detect vulnerabilities in programs.The current research on fuzzing technology focuses on the design of mutation operators and program analysis,and the collaborative scheduling between mutation operators has not been studied in depth.The article first studies 15 mutation operators commonly used in fuzzy testing,and analyzes the mutation efficiency of different mutation operators in different types of programs.Based on the exploration and utilization model,the article designs the mutation operator scheduling optimization model EE-POS based on the lawof mutation operator mutation efficiency to improve the vulnerability mining efficiency of the fuzzing technology.The article implements the EE-POS scheduling model on the prototype system EE-POS-AFL.The comparison with AFL shows that the path exploration efficiency of EE-POS-AFL is increased by 63%,and the vulnerability detection efficiency is increased by 153%.