Predicting Cyber-Trafficking Websites Using a Naive Bayes Algorithm, Logistic Regression, KNN, and SVM-Reference-Cited by-同舟云学术

Predicting Cyber-Trafficking Websites Using a Naive Bayes Algorithm, Logistic Regression, KNN, and SVM

Published:2023-11-11 Issue: Volume: Page:61-71
ISSN:1860-4862
Container-title:6th International Conference on Signal Processing and Information Communications
language:
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Author:

Sulit Aiza Jane,Acerado Risty,Tomaquin Ramon Christus,Morco Roselia

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43781-6_6

Reference22 articles.

1. Stop The Traffik. Definition and Scale.Learn more about human trafficking and how prevalent this fast-growing crime is. 2022. Retrieved in February, 2023. https://www.stopthetraffik.org/what-is-human-trafficking/definition-and-scale/

2. United Nations Office on Drugs and Crime (UNODC). Global report on trafficking in persons. 2009. Retrieved in February 2023. https://www.unodc.org/unodc/en/press/releases/2023/January/global-report-on-trafficking-in-persons-2022.html

3. U.S. Department of State. Trafficking in persons report: Philippines. 2022. Retrieved in February 2023. https://www.state.gov/reports/2022-trafficking-in-persons-report/philippines__trashed/

4. M. Latonero. Human trafficking online: the role of social networking sites and online classifieds. Center on Communication Leadership & Policy. Research Series: September 2011. USC. Annenberg School for communication & Journalism https://doi.org/10.2139/ssrn.2045851

5. J. Brunner. Getting to good human trafficking data. Assessing the landscape in Southeast Asia and promising practices from ASEAN governments and civil society. 2018. Retrieved in February 2023. https://humanrights.stanford.edu/sites/humanrights/files/good_ht_data_policy_report_final.pdf