A Novel Approach for Detection and Analysis of Malware for Smart Devices

Abstract

Smartphones are used to initiate the intervention of humans with machines. Therefore, newlinelow-cost hardware and high-speed internet make smartphones ubiquitously crucial in newlineany process. Almost everyone uses a smartphone with an android-based operating newlinesystem for more manageable growth in daily life and several business applications. The newlinehigher connectivity of billions of smartphone users creates serious security threats to newlinethe Android operating system. The versatile coverage and easier accessibility of every newlineapplication make the android system a key target for attackers. There are several newlineapplications in daily life, like bank transactions, etc., that require full details of senders newlineand receivers stored somewhere in the cloud. In our study of several research articles newlinefound in the Android ecosystem, there are various defies to analyze Android Malware newlineApps. Normally an attacker downloads various popular APKs from the google playstore disassembles the downloaded Apk, embeds it with malicious code (malware code newlineor adware code) assembles it into Repackaged App, and uploads it to a third party. newlineIn such repackage android systems (such as smart watches, palm devices, smart TV, newlineMobiles, recent IOT Devices, etc.), there was a need to detect the malware. there have newlinebeen various defies to identifying Android malware. Most existing outmoded systems newline(such as static, dynamic, and hybrid approaches proposed by many researchers during newlinethe last decade needed a high rate of human intervention which needs the inspection of newlineAPK file structures, which has amounting to increased computation time, high newlineprocessing power, more storage space and time-consuming. newline