Perspectives on Adversarial Classification

被引：4

作者：

Insua, David Rios ^{[1
,2
]}

Naveiro, Roi ^{[2
]}

Gallego, Victor ^{[2
]}

机构：

[1] Univ Shanghai Sci & Technol, Sch Management, Shanghai 201206, Peoples R China

[2] CSIC, ICMAT, Madrid 28049, Spain

来源：

MATHEMATICS | 2020年 / 8卷 / 11期

基金：

欧盟地平线“2020”;

关键词：

classification; adversarial machine learning; security; robustness; adversarial risk analysis; RISK ANALYSIS;

D O I：

10.3390/math8111957

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Adversarial classification (AC) is a major subfield within the increasingly important domain of adversarial machine learning (AML). So far, most approaches to AC have followed a classical game-theoretic framework. This requires unrealistic common knowledge conditions untenable in the security settings typical of the AML realm. After reviewing such approaches, we present alternative perspectives on AC based on adversarial risk analysis.

引用

页码：1 / 21

页数：21

共 50 条

[41] Adversarial Robustness Guarantees for Classification with Gaussian Processes
Blaas, Arno
Patane, Andrea
Laurenti, Luca
Cardelli, Luca
Kwiatkowska, Marta
Roberts, Stephen
INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 108, 2020, 108 : 3372 - 3381
[42] Generative Adversarial Networks in Retinal Image Classification
Mercaldo, Francesco
Brunese, Luca
Martinelli, Fabio
Santone, Antonella
Cesarelli, Mario
APPLIED SCIENCES-BASEL, 2023, 13 (18):
[43] Modified generative adversarial networks for image classification
Zhao, Zhongtang
Li, Ruixian
EVOLUTIONARY INTELLIGENCE, 2023, 16 (06) : 1899 - 1906
[44] Approaching Adversarial Example Classification with Chaos Theory
Pedraza, Anibal
Deniz, Oscar
Bueno, Gloria
ENTROPY, 2020, 22 (11) : 1 - 24
[45] Feature Cross-Substitution in Adversarial Classification
Li, Bo
Vorobeychik, Yevgeniy
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 27 (NIPS 2014), 2014, 27
[46] Adversarial Prototype Learning for Hyperspectral Image Classification
Wang, Shuai
Du, Bo
Zhang, Dingwen
Wan, Fang
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
[47] A Game Model for Adversarial Classification in Spam Filtering
Deng, Wei
Qu, Zehui
Ye, Li
Qin, Zhiguang
MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8, 2012, 433-440 : 5053 - 5057
[48] Adversarial Reprogramming of Text Classification Neural Networks
Neekhara, Paarth
Hussain, Shehzeen
Dubnov, Shlomo
Koushanfar, Farinaz
2019 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING AND THE 9TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (EMNLP-IJCNLP 2019): PROCEEDINGS OF THE CONFERENCE, 2019, : 5216 - 5225
[49] Adversarial Mobility Learning for Human Trajectory Classification
Gao, Qiang
Zhang, Fengli
Yao, Fuming
Li, Ailing
Mei, Lin
Zhou, Fan
IEEE ACCESS, 2020, 8 (08): : 20563 - 20576
[50] A Review of Adversarial Attack and Defense for Classification Methods
Li, Yao
Cheng, Minhao
Hsieh, Cho-Jui
Lee, Thomas C. M.
AMERICAN STATISTICIAN, 2022, 76 (04): : 329 - 345

← 1 2 3 4 5 →