Modeling and Analysis of Intentional And Unintentional Security Vulnerabilities in a Mobile Platform Page: 25
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Benign Applications - With Class Labels
Business 59
Communication 61
Finance 60
Games 61
Media&Video 63
Medical 59
Music&Audio 62
Photography 60
Productivity 64
Transportation 64
Other 68
Sub Total 681
Benign Applications - Unlabeled 1049
Malware Samples (In 49 families) 273
Total 2003
TABLE 4.1. The datasets for intention based potential malware identification.
The malware data set obtained from NCSU originally consisted of 1,260 android malware
(APK) samples from 49 different malware families. This particular dataset is imbalanced with
some malware families having close to 300 samples over others with only one sample. Thus, for
uniformity, I restricted the number of samples to 10 per family, yielding a total of 273 malware
samples from 47 malware families in the final malware dataset.
First a smaller collection of Android apps were manually downloaded from Google Play. I
collected about 681 apps to construct this dataset. All these application samples were labeled with
its intention class.
Then, I improved the smaller benign dataset further by downloading additional benign25
I
Data Set
Count
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Mohamed Issadeen, Mohamed Fazeen. Modeling and Analysis of Intentional And Unintentional Security Vulnerabilities in a Mobile Platform, dissertation, December 2014; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc700067/m1/39/: accessed July 18, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .