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 to deceive the discriminator, thus achieve the defense against malicious code attacks and improve malware detection. Firstly, a new Android malware APK to image texture feature extraction segmentation method is proposed, which is called segment self-growing texture segmentation algorithm. Secondly, tensor singular value decomposition (tSVD) based on the low-tubal rank transforms malicious features with different sizes into a fixed third-order tensor uniformly, which is entered into the neural network for training and learning. Finally, a flexible Android malware detection model based on GANs with code tensor (MTFD-GANs) is proposed. Experiments show that the proposed model can generally surpass the traditional malware detection model, with a maximum improvement efficiency of 41.6\%. At the same time, the newly generated samples of the GANs generator greatly enrich the sample diversity. And retraining malware detector can effectively improve the detection efficiency and robustness of traditional models.
翻译:恶意软件威胁的行为正在逐渐增加,增加了对恶意软件检测的需要。然而,现有的恶意软件检测方法仅针对现有的恶意样本,检测新的恶意代码和恶意代码的变异功能有限。在本文中,我们提出了一个新办法,以高效检测恶意软件及其变异。根据基因对抗网络(GANs)的理念,我们获得了满足真实恶意软件特征的“真实”样本分布,利用它们来欺骗导师,从而实现防止恶意代码袭击的防御,并改进恶意软件的检测。首先,提出了一个新的Andromod恶意软件APK到图像质谱特征提取分解方法,即所谓的部分自我增长质谱分解算法。第二,基于低语级将不同尺寸的恶意特征转化为固定的三等强调,并输入神经机网络,用于培训和学习。最后,一个基于GANs(MTFD-GANs)的软质软件到图像质谱质谱提取特性分解方法。根据低调标准,高压单值分解分解(ts sal las mestal sestal sestal resmissational laveal) ex recal laveal supal ex real supal suplational supal supal preal)。 6 exal sal sal laveal sal sal saldaldal sal laveal exaldaldaldaldal ex exmal. shal 可以提出, exmentaldal a ex exmal exaldaldaldaldaldaldaldaldaldaldaldald.