暂无分享,去创建一个
Zhi Xue | Yong Shi | Zilong Lin | Zilong Lin | Zhi Xue | Yong-yu Shi
[1] Lior Rokach,et al. Low Resource Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers , 2018, ArXiv.
[2] Yi-Hsuan Yang,et al. MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment , 2017, AAAI.
[3] Christian Ledig,et al. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] H. Anderson,et al. Evading Machine Learning Malware Detection , 2017 .
[5] Liang Hu,et al. An improved intrusion detection framework based on Artificial Neural Networks , 2015, 2015 11th International Conference on Natural Computation (ICNC).
[6] Ying Tan,et al. Black-Box Attacks against RNN based Malware Detection Algorithms , 2017, AAAI Workshops.
[7] Léon Bottou,et al. Wasserstein GAN , 2017, ArXiv.
[8] Salvatore J. Stolfo,et al. A framework for constructing features and models for intrusion detection systems , 2000, TSEC.
[9] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .
[10] Abdullah Al-Dujaili,et al. Adversarial Deep Learning for Robust Detection of Binary Encoded Malware , 2018, 2018 IEEE Security and Privacy Workshops (SPW).
[11] Wei-Yang Lin,et al. Intrusion detection by machine learning: A review , 2009, Expert Syst. Appl..
[12] Jungwoo Lee,et al. Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN , 2017, ArXiv.
[13] Yun Chen,et al. Dialogue Generation With GAN , 2018, AAAI.
[14] Kai Huang,et al. Intrusion Detection Using Convolutional Neural Networks for Representation Learning , 2017, ICONIP.
[15] Bhavani M. Thuraisingham,et al. Adversarial support vector machine learning , 2012, KDD.
[16] Sung-Bae Cho,et al. Malware Detection Using Deep Transferred Generative Adversarial Networks , 2017, ICONIP.
[17] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[18] Patrick D. McDaniel,et al. Adversarial Perturbations Against Deep Neural Networks for Malware Classification , 2016, ArXiv.
[19] David Wagner,et al. Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods , 2017, AISec@CCS.
[20] Andrew J. Clark,et al. Data preprocessing for anomaly based network intrusion detection: A review , 2011, Comput. Secur..
[21] Ying Tan,et al. Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN , 2017, DMBD.
[22] Zhi Xue,et al. Character-Level Intrusion Detection Based On Convolutional Neural Networks , 2018, 2018 International Joint Conference on Neural Networks (IJCNN).
[23] Lior Rokach,et al. Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers , 2017, RAID.