Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation

Zhang, Yongfeng; Tan, Yunzhi; Zhang, Min; Liu, Yiqun; Chua, Tat-Seng; Ma, Shaoping

Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation

Yongfeng Zhang, Yunzhi Tan, Min Zhang, Yiqun Liu, Tat-Seng Chua, Shaoping Ma

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Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 2408-2413.

Abstract

Many e-commerce systems allow users to express their opinions towards products through user reviews systems. The user generated reviews not only help other users to gain a more insightful view of the products, but also help online businesses to make targeted improvements on the products or services. Besides, they compose the key component of various personalized recommender systems. However, the existence of spam user accounts in the review systems introduce unfavourable disturbances into personalized recommendation by promoting or degrading targeted items intentionally through fraudulent reviews. Previous shilling attack detection algorithms usually deal with a specific kind of attacking strategy, and are exhausted to handle with the continuously emerging new cheating methods. In this work, we propose to conduct shilling attack detection for more informed recommendation by fraudulent action propagation on the reviews themselves, without caring about the specific underlying cheating strategy, which allows us a unified and flexible framework to detect the spam users.

Yongfeng Zhang, Yunzhi Tan, Min Zhang, Yiqun Liu, Tat-Seng Chua, and Shaoping Ma. 2015. Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 2408–2413. https://ijcai.org/proceedings/2015/341

@inproceedings{ijcai2015p341,
  title     = {Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation},
  author    = {Zhang, Yongfeng and Tan, Yunzhi and Zhang, Min and Liu, Yiqun and Chua, Tat-Seng and Ma, Shaoping},
  booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-15}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Qiang Yang and Michael Wooldridge},
  pages     = {2408--2413},
  year      = {2015},
  month     = {7},
  note      = {Main Track},
  url       = {https://ijcai.org/proceedings/2015/341},
}

TY  - CPAPER
TI  - Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation
AU  - Zhang, Yongfeng
AU  - Tan, Yunzhi
AU  - Zhang, Min
AU  - Liu, Yiqun
AU  - Chua, Tat-Seng
AU  - Ma, Shaoping
T2  - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2015
SP  - 2408
EP  - 2413
UR  - https://ijcai.org/proceedings/2015/341
ER  -