
With the smartphones entering our lives, the number of smartphones continues to increase day by day. The reason why smartphones are in so demand is that people can easily do what they want. According to IDC's 2016 Q2 report, Android dominated the smartphone market with an 87.6% share [1]. The Android platform has become the number one target of malicious people because of Android has an open source and new application installation has not been analyzed in detail. Therefore, the number of Android malicious applications are also increasing every day on Google Play and alternative Android application markets. According to G Data's 2015 Q1 mobile malware report, 50.3% of malware is for financial purposes [2]. The reason is that 41% of Europe's users use their devices for banking transactions [2]. Hence, there is need for effective malware detection systems which are detect malicious software on Android application markets. In this paper, malicious software detection systems will be explained.
Technology, Science (General), mobil güvenlik 6, T, Science, Q, android uygulama güvenliği 4, android security 5, Engineering (General). Civil engineering (General), android güvenliği 5, android 1, Q1-390, akıllı telefon 3, malware detection 2, smartphone 3, mobile security 6, TA1-2040, kötücül yazılım tespiti 2, android application security 4
Technology, Science (General), mobil güvenlik 6, T, Science, Q, android uygulama güvenliği 4, android security 5, Engineering (General). Civil engineering (General), android güvenliği 5, android 1, Q1-390, akıllı telefon 3, malware detection 2, smartphone 3, mobile security 6, TA1-2040, kötücül yazılım tespiti 2, android application security 4
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
