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RUP-GAN:A Black-Box Attack Method for Social Intelligence Recommendation Systems Based on Adversarial Learning

Siyang Yu Mingxing Duan Kezhi Wang Shenghong Yang

大数据挖掘与分析（英文版）2025，Vol.8Issue(4)：820-836,17.

大数据挖掘与分析（英文版）2025，Vol.8Issue(4)：820-836,17.DOI:10.26599/BDMA.2025.9020002

RUP-GAN:A Black-Box Attack Method for Social Intelligence Recommendation Systems Based on Adversarial Learning

Siyang Yu ¹Mingxing Duan ²Kezhi Wang ³Shenghong Yang³

作者信息

1. College of Information Technology and Management,Hunan University of Finance and Economics Changsha 410000,China||School of Information Science and Engineering,Hunan University,Changsha 410000,China
2. School of Information Science and Engineering and Key Laboratory of Fusion Computing of Supercomputing and Artificial Intelligence of Ministry of Education,Hunan University,Changsha 410000,China||Shenzhen Institute,Hunan University,Shenzhen 518063,China
3. School of Information Science and Engineering,Hunan University,Changsha 410000,China
折叠

摘要

关键词

Social Intelligence Recommendation Systems(SIRS)/Generative Adversarial Networks(GAN)/shilling attacks

Key words

Social Intelligence Recommendation Systems(SIRS)/Generative Adversarial Networks(GAN)/shilling attacks

引用本文复制引用

Siyang Yu,Mingxing Duan,Kezhi Wang,Shenghong Yang..RUP-GAN:A Black-Box Attack Method for Social Intelligence Recommendation Systems Based on Adversarial Learning[J].大数据挖掘与分析（英文版）,2025,8(4):820-836,17.

基金项目

This work was supported by the Program of National Natural Science Foundation of China(Nos.62472151,U24A20255,62422205,62272149,and U23A20317),the Program of Natural Science Foundation of Hunan(No.2023JJ30102),the Science and Technology Innovation Program of Hunan Province(No.2022RC1038),the Natural Science Foundation of Hunan Province(No.2023JJ40162),the Shenzhen Science and Technology Program(No.JCYJ20210324141208020),the Natural Science Foundation of Hunan Province(Nos.2023JJ10016 and 2023JJ30083),and the Yuelu Mountain Industrial Innovation Center Project(No.2023YCII0118). （Nos.62472151,U24A20255,62422205,62272149,and U23A20317）

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