基于免疫和代码重定位的计算机病毒特征码提取与检测方法
发布时间：2018-09-01 19:07
【摘要】：针对当前感染率高、威胁性极大的感染型计算机病毒,提出了一种基于免疫和代码重定位的计算机病毒特征码提取与检测方法.借鉴生物免疫系统机理,定义了计算机系统中的自体、非自体、抗体、病毒检测器、病毒基因等免疫概念,利用感染型病毒独特的代码重定位特性来提取病毒基因、构建病毒基因库,并在此基础上建立了自体/非自体、病毒基因库和病毒检测器动态演化模型.理论分析与实验结果表明,本方法有效克服了传统方法存在的自体集完备性问题和病毒检测器抗体完整性问题,因而比传统方法有更好的效率与适应性.
[Abstract]:In view of the high infection rate and great threat, a method of extracting and detecting the signature of computer virus based on immune and code relocalization is proposed. Referring to the mechanism of biological immune system, the immune concepts of autogenous, non-autogenous, antibody, virus detector, virus gene and so on in computer system are defined, and the virus gene is extracted by using the unique code relocalization characteristics of infected virus. Based on the construction of virus gene bank, the dynamic evolution model of autologous / non-autologous virus gene bank and virus detector was established. The theoretical analysis and experimental results show that this method can effectively overcome the self-set completeness problem and the virus detector antibody integrity problem, so it has better efficiency and adaptability than the traditional method.
【作者单位】： 海南师范大学信息学院;Department
【基金】：国家自然科学基金资助项目(61462025,61262077,61363032,61463012) 海南省重点研发计划资助项目(ZDYF2016013)
【分类号】：TP309.5
，
本文编号：2218081
[Abstract]:In view of the high infection rate and great threat, a method of extracting and detecting the signature of computer virus based on immune and code relocalization is proposed. Referring to the mechanism of biological immune system, the immune concepts of autogenous, non-autogenous, antibody, virus detector, virus gene and so on in computer system are defined, and the virus gene is extracted by using the unique code relocalization characteristics of infected virus. Based on the construction of virus gene bank, the dynamic evolution model of autologous / non-autologous virus gene bank and virus detector was established. The theoretical analysis and experimental results show that this method can effectively overcome the self-set completeness problem and the virus detector antibody integrity problem, so it has better efficiency and adaptability than the traditional method.
【作者单位】： 海南师范大学信息学院;Department
【基金】：国家自然科学基金资助项目(61462025,61262077,61363032,61463012) 海南省重点研发计划资助项目(ZDYF2016013)
【分类号】：TP309.5
，
本文编号：2218081
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