… calls features, assembly features, and binary features are … Signature-based strategies depend
in light of exceptional crude … position in the established samples. The created information …

… intelligent malware detection approaches critically depend … feature extraction and the
classification/clustering techniques. … points or position vectors in a multidimensional feature space. …

… a classical data mining rationale. As for most behavior-based malware detection approaches,
… mon sub-graphs on kernel object dependency graphs, to capture characteristic behavior of …

… malware detection by selecting the best features using PSO … and graph based on data and
control dependency is constructed and … Their work used data mining techniques for searching …

… degree of dependency between the different feature sets and … relevant, although their position
in the ranking may change. … of the process category is the most informative feature, even …

… kinds of input features used for malware detection will be … The final data mining model [1]
had a detection rate double … the existence of a feature regardless of its position. Barker et al. …

… rules of apriori algorithm for feature extraction and signature … swarm optimization through
data mining technique with modified … The particle’s velocity and position in an updated standard …

… malware, and permission features utilized as effective … straightforward machine learning
techniques that depend on the … of malware detection approaches using data mining techniques.…

… Based on the dependency graphs of malware samples, the common behavior graph was
extracted and used to represent the behavioral features of a malware … the beginning position as …

… behaviours of malware, resemblance-oriented mining and Machine Learning algorithms are
used [14]. It is dependent on … Data mining methods are utilized for extracting the features of …