Android Malware Classification Using LSTM Model
Nagababu Pachhala, Subbaiyan Jothilakshmi, Bhanu Prakash Battula · Revue d intelligence artificielle · 2022
From last two decades, smartphone use is essentially widespread around the world, and Android is the most popular open-source operating system, with the largest market share and active user population of any open-source operating system. This has resulted in malicious actors turning their attention toward the Android operating system to exploit user reliance and vulnerabilities that exist inside the system. Hackers can take advantage of consumers' sensitive data to engage in advertising, extortion, and theft. Most of the existing anti-malware software’s cannot be able to detect all the malwares because of the intelligent malwares. In this paper we use the deep learning based Long short-term memory (LSTM) network for android malware classification. The model is effective in classification of intelligent malwares. The proposed model is implemented using google colab. The model is archiving more than the 98% accuracy in classification of android malwares.