Shilling attack detection based on improved clustering algorithm

Yao Ma; Xuesong Su; Wenguang Zheng; Li Liu

doi:10.1117/12.2660939

2 February 2023 Shilling attack detection based on improved clustering algorithm

Yao Ma, Xuesong Su, Wenguang Zheng, Li Liu

Proceedings Volume 12462, Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022); 124622N (2023) https://doi.org/10.1117/12.2660939
Event: International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022), 2022, Xi'an, China

Abstract

Recommendation system is becoming increasingly important in various fields of life. To guarantee the accuracy of recommendation, the detection of shilling attacks must be considered. However, the performance of the existing detection techniques for shilling attacks is relatively low, especially for unknown types of attacks, the existing detection techniques are not universal. In this paper, we propose an improved clustering algorithm-based shilling attacks detection method. This method uses information entropy to select a feature and uses the selected feature to calculate the similarity between two users in the clustering algorithm. Experiments show that the algorithm has good detection performance in the detection of shilling attacks.

Citation Download Citation

Yao Ma, Xuesong Su, Wenguang Zheng, and Li Liu "Shilling attack detection based on improved clustering algorithm", Proc. SPIE 12462, Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022), 124622N (2 February 2023); https://doi.org/10.1117/12.2660939

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KEYWORDS

Detection and tracking algorithms

Distributed interactive simulations

Feature selection

Lithium

Feature extraction

Inspection

Network architectures

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