Flexible Android Malware Detection Model based on Generative Adversarial Networks with Code Tensor. (arXiv:2210.14225v1 [cs.CR])

The behavior of malware threats is gradually increasing, heightened the need
for malware detection. However, existing malware detection methods only target
at the existing malicious samples, the detection of fresh malicious code and
variants of malicious code is limited. In this paper, we propose a novel scheme
that detects malware and its variants efficiently. Based on the idea of the
generative adversarial networks (GANs), we obtain the `true' sample
distribution that satisfies the characteristics of the real malware, use them …

adversarial android android malware code detection generative adversarial networks malware malware detection networks tensor