Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18490
Title: Systematic Literature Review on Application Program Interface based Android Malware Detection
Authors: Ehoda, Emmanuel
Adebayo, Olawale Surajudeen
Ismaila, Idris
Ojeniyi, Joseph
Olalere, Morufu
Keywords: Android Malware Detection
API Call Features
Deep Learning
Android Malware Review
Malware Analysis
Issue Date: 22-Mar-2023
Abstract: Over the years, various malware detection approaches have been proposed in a bid to address evolving malware threats landscape in android operating system. Systematic literature reviews to analyze these detection approaches have been carried out, but none have been tailored to identifying challenges with android malware detection based on the use of Android program interface (API) features, hence there is no aggregated information on what work has been done by researchers in this area. This research, therefore, presents a systematic literature review on API feature based android malware detection literatures between 2018 to 2022 collected systematically using PRISMA frameworks. This study is able to identify the challenges faced in android malware detection over the years, methodologies used to address them and limitations of API based feature detection. These useful insights documented in this research will serve as valuable resources which researchers can leverage on to improve the detection of android malware.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18490
Appears in Collections:Cyber Security Science

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