Detection of Malware in Android Application using Machine Learning

Detection of Malware in Android Application using Machine Learning

Paka Sudarsan, V.N V S K Vinay, Rejeti Pavan Satya Kumar, Burugupalli Jagadeesh,

Guide : Maddipati Satya Srinivas, Associate Professor

Department of Computer Science and Engineering
Sasi Institute of Technology and Engineering

Abstract - Malware is a piece of software which contains malicious data which damage or disrupt a device's normal use it is intentionally created to exploit systems without the user's knowledge. Since there is a rapid increase in mobile usage especially android ones has changed the way user access information and perform daily tasks as there is a large increase in human usage, malware also gets proportionately increased With the increasing complexity and diversity of malware, it is difficult for traditional methods  to identify them This study explain nature of malware and various forms, including viruses, worms, Trojans, ransomware, adware, spyware, and rootkits. Where each attack has a different way of injecting malware into android environment. Since traditional methods tries to identify known malware signatures, they tend to fail in predicting new attacks The primary objective of this paper is to utilise ML models especially logistic regression as it is a binary classification model which can handle classification problems well, and make a effective malware prediction model.

Index Terms - Malware, machine learning, android applications, logistic regression