Chinese Spam Filter under Adversarial Impact

DOI

10.2991/icmmcce-15.2015.562How to use a DOI?

Keywords

Anti-spam, Machine Learning, Adversarial Attacks, Adversarial Impact

Abstract

Machining learning techniques have achieved great success in anti-spam area. But because of the limitations of these techniques, classifiers derived from them often get attacked by spam senders thus posing a threat to the whole Spam filtering system. This article briefly describes the type of attacks to classifiers and then simulates an attack on a public Chinese spam corpus to analyze the adversarial impact of several major classifiers.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yaqing Zhao
AU  - Yan Xu
AU  - Xiaodan Zhao
PY  - 2015/12
DA  - 2015/12
TI  - Chinese Spam Filter under Adversarial Impact
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.562
DO  - 10.2991/icmmcce-15.2015.562
ID  - Zhao2015/12
ER  -