An entropy-based distance measure for analyzing and detecting metamorphic malware
作者:Esmaeel Radkani, Sattar Hashemi, Alireza Keshavarz-Haddad, Maryam Amir Haeri
摘要
Metamorphic malware is a kind of malware which evades signature-based anti-viruses by changing its internal structure in each infection. This paper, firstly, introduces a new measure of distance between two computer programs called program dissimilarity measure based on entropy (PDME). Then, it suggests a measure for the degree of metamorphism, based on the suggested distance measure. The distance measure is defined based on the Entropy of the two malware programs. Moreover, the paper shows that the distance measure can be used for classifying metamorphic malware via K-Nearest Neighbors (KNN) method. The method is evaluated by four metamorphic malware families. The results demonstrate that the measure can indicate the degree of metamorphism efficiently, and the KNN classification method using PDME can classify the metamorphic malware with a high precision.
论文关键词:Metamorphic malware, Entropy, Distance, Degree of metamorphism, K-nearest neighbors, Malware detection
论文评审过程:
论文官网地址:https://doi.org/10.1007/s10489-017-1045-6