ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS

İhsan Güneş; Mustafa Kemal Birgin

doi:10.18038/estubtda.1672606

EN

ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS

Abstract

Privacy-preserving collaborative filtering (PPCF) denotes a methodology that recommends items to users according to their interests or behaviors while safeguarding user privacy and data confidentiality. PPCF is especially crucial in situations involving sensitive user data, such as purchase history, surfing activity, or personal preferences. Privacy-preserving model-based recommendation methods are preferred over privacy-preserving memory-based schemes due to their online efficiency. There is a lot of work in the literature on model-based CF and PPCF schemes. Model-based prediction algorithms without privacy concerns have been adequately studied in terms of shilling attacks. However, there is a limited number of studies that measure the robustness of model-based PPCF schemes against shilling attacks. PPCF schemes can also be affected by shilling attacks, as can model-based prediction algorithms without privacy concerns. In this study, we investigate the robustness of genetic algorithm based PPCF schemes against shilling attacks. In this paper firstly, we apply masked data-based profile injection attacks to genetic algorithm-based PPCF prediction algorithms. Then, we perform extensive experiments using real data to evaluate their robustness against profile injection attacks. We then compare other model-based methods that have been studied in the literature in terms of robustness. Our empirical analyses show that the model-based scheme with privacy is very robust against shilling attacks.

Keywords

Genetic algorithms, Collaborative filtering, Privacy, Recommendation system, Shilling attacks

References

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Details

Primary Language

English

Subjects

Machine Learning Algorithms

Journal Section

Research Article

Authors

İhsan Güneş ^*
0000-0001-5932-8068
Türkiye

Mustafa Kemal Birgin
0000-0003-0370-7143
Türkiye

Publication Date

September 25, 2025

Submission Date

April 9, 2025

Acceptance Date

July 10, 2025

Published in Issue

Year 2025 Volume: 26 Number: 3

DOI

https://doi.org/10.18038/estubtda.1672606

IZ

https://izlik.org/JA84UU79EG

APA

Güneş, İ., & Birgin, M. K. (2025). ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, 26(3), 246-259. https://doi.org/10.18038/estubtda.1672606

AMA

1.Güneş İ, Birgin MK. ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS. Estuscience - Se. 2025;26(3):246-259. doi:10.18038/estubtda.1672606

Chicago

Güneş, İhsan, and Mustafa Kemal Birgin. 2025. “ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 26 (3): 246-59. https://doi.org/10.18038/estubtda.1672606.

EndNote

Güneş İ, Birgin MK (September 1, 2025) ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 26 3 246–259.

IEEE

[1]İ. Güneş and M. K. Birgin, “ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS”, Estuscience - Se, vol. 26, no. 3, pp. 246–259, Sept. 2025, doi: 10.18038/estubtda.1672606.

ISNAD

Güneş, İhsan - Birgin, Mustafa Kemal. “ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 26/3 (September 1, 2025): 246-259. https://doi.org/10.18038/estubtda.1672606.

JAMA

1.Güneş İ, Birgin MK. ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS. Estuscience - Se. 2025;26:246–259.

MLA

Güneş, İhsan, and Mustafa Kemal Birgin. “ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, vol. 26, no. 3, Sept. 2025, pp. 246-59, doi:10.18038/estubtda.1672606.

Vancouver

1.İhsan Güneş, Mustafa Kemal Birgin. ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS. Estuscience - Se. 2025 Sep. 1;26(3):246-59. doi:10.18038/estubtda.1672606

Abstract

ROBUSTNESS ANALYSIS OF GENETIC ALGORITHM-BASED PRIVACY-PRESERVING RECOMMENDATION ALGORITHMS

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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