This dataset is a result of my research production in machine learning and android security. The data were obtained by a process that consisted to create a binary vector of permissions used for each application analyzed {1=used, 0=no used}. Moreover,  the samples of malware/benign were devided by "Type"; 1 malware and 0 non-malware.

One important topic to work is to create a good set of malware, because it is difficult to find one updated and with a research work to support it .

If your papers or other works use our dataset, please cite our COLCOM 2016 paper as follows.
Urcuqui, C., & Navarro, A. (2016, April). Machine learning classifiers for android malware analysis. In Communications and Computing (COLCOM), 2016 IEEE Colombian Conference on (pp. 1-6). IEEE.

If you need an article in english, you can download another of my works:
Urcuqui, Christian., & Navarro, Andres. (2016). framework for malware analysis in Android. Sistemas & Telemática, 14(37), 45-56.

ccurcuqui@icesi.edu.co