An Android Malware Detection Method Using Deep Learning Based on API Calls

ieee advanced information management communicates electronic and automation control conference(2019)

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摘要
With the in-depth development of the Internet industry, the mobile Internet has been effectively integrated into daily work. However, Android has many extremely serious security issues. In our work, we apply text classification technology to the detection of Android malware, based on the deep learning. We extract the Android malware API sequence based on the Cuckoo sandbox, and use the text processing technology to solve the detection problem of Android malware. To evaluating the performance of our system, we compared it with Dalvik based on the Bi-LSTM. The accuracy of API extraction method using Cuckoo is higher than Dalvik, reaching the accuracy of 96.74%. To further verify the effects of different models, we compared it with GRU, BGRU and LSTM using Cuckoo Sandbox as API extraction method. The result demonstrate the Bi-LSTM has the highest accuracy.
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关键词
Android,malware classification,Bi-LSTM,deep learning
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