  Android devices are growing exponentially and are connected through the
internet accessing billion of online websites. The popularity of these devices
encourages malware developer to penetrate the market with malicious apps to
annoy and disrupt the victim. Although, for the detection of malicious apps
different approaches are discussed. However, proposed approaches are not
suffice to detect the advanced malware to limit/prevent the damages. In this,
very few approaches are based on opcode occurrence to classify the malicious
apps. Therefore, this paper investigates the five classifiers using opcodes
occurrence as the prominent features for the detection of malicious apps. For
the analysis, we use WEKA tool and found that FT detection accuracy (79.27%) is
best among the investigated classifiers. However, true positives rate i.e.
malware detection rate is highest (99.91%) by RF and fluctuate least with the
different number of prominent features compared to other studied classifiers.
The analysis shows that overall accuracy is majorly affected by the false
positives of the classifier.
