Adversarial Machine Learning for Text

被引：4

作者：

Lee, Daniel ^{[1
]}

Verma, Rakesh ^{[1
]}

机构：

[1] Univ Houston, Houston, TX 77004 USA

来源：

PROCEEDINGS OF THE SIXTH INTERNATIONAL WORKSHOP ON SECURITY AND PRIVACY ANALYTICS (IWSPA'20) | 2020年

关键词：

adversarial examples; adversarial text; neural networks; natural language processing; deep learning;

D O I：

10.1145/3375708.3380551

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this tutorial, we investigate the history, evolution and latest research topics in the area of adversarial machine learning for text data. Both classical attacks on spam filters and more recent attacks on deep learning models for text classification problems will be discussed. We then discuss proposed and potential defenses against these attacks. We conclude with some directions for future research.

引用

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页码：33 / 34

页数：2

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