Application of machine learning to identify Counterfeit Website

Author:

Wu KuanTing1,Chou ShingHua2,Chen ShyhWei3,Tsai ChingTsorng4,Yuan ShyanMing2

Affiliation:

1. Institute of Network Engineering, National Chiao Tung University, Hsinchu, Taiwan

2. Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan

3. Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan

4. Department of Computer Science, Tunghai University, Taichung, Taiwan

Publisher

ACM

Reference15 articles.

1. The E-Commerce Market for "Lemons"

2. Learning to detect and measure fake ecommerce websites in search-engine results

3. Digital Advertising Ecosystem. {Online}. Available: https://hsienblog.com/2017/06/25/%E6%95%B8%E4%BD%8D%E5%BB%A3%E5%91%8A%E6%9E%B6%E6%A7%8B-rtb-dsp-ssp-dmp-ad-exchange-adnetwork/ Digital Advertising Ecosystem. {Online}. Available: https://hsienblog.com/2017/06/25/%E6%95%B8%E4%BD%8D%E5%BB%A3%E5%91%8A%E6%9E%B6%E6%A7%8B-rtb-dsp-ssp-dmp-ad-exchange-adnetwork/

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1. Online counterfeiting in the e-commerce of luxury goods and the role of business intelligence: A systematic mapping study;2024-01-17

2. Fraudulent E-Commerce Website Detection Using Convolutional Neural Network Based on Image Features;Lecture Notes on Data Engineering and Communications Technologies;2024

3. E-Commerce and Cybersecurity Challenges;Handbook of Research on Cybersecurity Issues and Challenges for Business and FinTech Applications;2022-10-21

4. Development of Machine Learning Based Fraudulent Website Detection Scheme;2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII );2022-07-22

5. Detection of Fake Educational Sites Using Fuzzy String Match;2022 2nd International Conference on Technology Enhanced Learning in Higher Education (TELE);2022-05-26

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