机译:针对深度神经网络分类的对抗学习:针对攻击的防御方法的全面综述
Penn State Univ Sch Elect Engn & Comp Sci University Pk PA 16802 USA;
Training data; Neural networks; Reverse engineering; Machine learning; Robustness; Training data; Feature extraction; Social networking (online); Informatics; Adversarial machine learning; Anomaly detection (AD); backdoor; black box; data poisoning (DP); deep neural networks (DNNs); membership inference attack; reverse engineering (RE); robust classification; targeted attacks; test-time-evasion (TTE); transferability; white box;
机译:评估对遥感场景分类深度神经网络的对抗例的威胁:攻击和防御
机译:针对深度神经网络的对抗性攻击和防御:一项调查
机译:对医学图像分类深神经网络的普遍对抗攻击
机译:MTDeep:通过移动目标防御提高深层神经网络抵抗对抗攻击的安全性
机译:对深神经网络的对抗攻击
机译:对医学图像分类深神经网络的普遍对抗攻击
机译:深度神经网络的鲁棒性:综合建筑与体重初始化对对抗敏感性和可转移性的综合研究