• SUBHASH PRABHAKAR KAMATH
• VIKAS BODDU
• GOTTAPU TARAKA RAMA RAO

There is a serious growth in the number of malicious apps in the Internet. Over the past few years malware has become a serious threat to many smart phone users. To defend this high rate of growth we have to create a system to detect malware apps. Data mining is a concept which we had used to categorize data, there are various algorithms and concepts which we can use to split the apps in two categories- malware or benign. In this comparative study we had analyzed various algorithms in data mining to classify android apps. The dataset used in this paper contains various permissions requested by apps from various sources in which it contains 58,519 apps out of which 53,422 were benign apps and the remaining 5,097 were malware apps. In order to classify the android apps we had performed preprocessing to the data and applied classification techniques on the data using the permissions requested by them.

ANDRIOD,MALWARE,DATA MINING,CLASSIFICATION

"A STUDY ON ANDRIOD MALWARE USING VARIOUS DATA MINING CLASSIFICATION TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.332-338, August-2018, Available :http://www.jetir.org/papers/JETIR1808196.pdf

"A STUDY ON ANDRIOD MALWARE USING VARIOUS DATA MINING CLASSIFICATION TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp332-338, August-2018, Available at : http://www.jetir.org/papers/JETIR1808196.pdf