machine learning : 机器学习            

deep learning : 深度学习

image processing : 图像处理

natural language processing : 自然语言处理

algorithms : 算法

training data set : 训练数据集

facial detection : 面部识别

malware detection : 恶意程序检测

adversarial sample : 对抗样本

countermeasuring techniques : 防御技术

Indiscriminate Attack:非针对性攻击

Adversary’s goal:敌手目标

Adversary’s knowledge :敌手知识

Adversary’s capability:敌手能力

Attack strategy:攻击策略

Gradient Ascent Strategy:梯度下降策略

Generative Model:生成模型

Discriminative model:判别模型

The Direct Gradient:直接梯度法

Accuracy:准确率

Loss:损失值

White-Box Attack:白盒攻击

Blank-Box Attack:黑盒攻击

Reconstruction Attack:重建攻击

Proactive Defense:主动防御

Reactive Defense:被动防御

Reject On Negative Impact:拒绝消极影响

Stackelberg Games:斯塔克尔伯格博弈

Defensive Distillation:防御精馏

Differential Privacy:差分隐私

Homomorphic Encryption:同态加密

Pattern Recognition:模式识别

RNN, Recurrent Neural Networks:循环神经网络

FNNs(Feed-forward Neural Networks):前向反馈神经网络

Convolutional layer:卷积层

Rectified Linear Units layer,ReLU layer:线性整流层

Pooling layer :池化层

Fully-Connected layer:全连接层

      

Face Recognition System :面部识别系统 (FRS)

Adversarial Classification : 敌手分类

Adversarial Learning :对抗学习

try-and-error:试错

Causative Attack :诱发型攻击

Security Violation :安全损害

Integrity Attack :完整性攻击

Availability Attack:可用性攻击

Privacy Violation Attack :隐私窃取攻击

Specificity of an Attack :攻击的专一性

Obfuscation Attacks:迷惑攻击

Counterintuitive:反直觉

Poisoning Attack:投毒攻击

Centroid:中心值

Bridge:桥

Spoofing Attack :欺骗攻击

Avoiding Attack:逃避攻击

Impersonate Attack:模仿攻击

The Least Likely Class:最小相似类

Inversion Attack:逆向攻击

Confidence Values:置信值

Equation-Solving Attacks:等式求解攻击

Model Extraction Attacks:模型提取攻击

Arms Race:攻防技术竞赛

Non-stationary:不平稳

Data Sanitization:数据清洗

Randomized Prediction Games:随机预测博弈

Deep Contractive Networks:深度收缩网络

Crowdsourcing:众包

Randomized Response:随机响应

Logistic Regression:逻辑回归

regression analysis:回归分析