Review articleMalicious application detection in android — A systematic literature review
Section snippets
Introduction and motivation
With the addition of smart phones in day-to-day life, its involvement in our life gets increased. It is involved in all daily activities of a person:
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Whether it is phone call to friend/relative.
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Capturing a precious life moment.
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Doing any important bank transaction.
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Or storing valuable data to a digital storage place.
Now in these days, the utilization of mobile phones gets increased rapidly and it becomes source of all the things which were implemented/ executed by telephone, camera, computers and
Review method
Systematic literature review reported in the paper will include the following factors [28], [29], [30], [31]:
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Development of Review Protocol
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Conducting Review
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Analyzing the Results
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Reporting the Results
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Discussion of Findings
Current status of mobile operating systems used in market
In the era of digitalization, mobile phone is the primary need of majority of people. In these mobile phones, the category of smart phone is more famous than others because it can be used for multiple purposes like calling, SMS, storage, picture capturing and working on internet. There are numerous types of operating systems are available in the market that are used in these smart phones. But as per the report from [1], 75% of the world is using Google’s android operating system. The Fig. 5
Inferences
Fig. 18 shows the synthesis of literature review, it illustrates various detection techniques along with machine learning classification and datasets used. In this figure, we reported the studies which has used machine learning with any of detection technique. Two mostly used malware datasets are mentioned in the figure.
This section discusses some inferences from the literature review:
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Mostly static analysis techniques are used for malware detection as compared to other techniques. This is due
Conclusion and future research
To sum up, the review is conducted on 380 research papers which are identified from various international research articles from reputed electronic sources. The prime focus of study is to identify various android malicious application detection techniques. The results are presented in various forms such as tables, line charts, pie charts, flow diagrams and mapping table. It is found that detection system is divided into three categories: Static, dynamic and hybrid. It is identified that both
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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