Cosine and Soft Cosine Similarity-Based Anti-Phishing Model
Author:
Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-33-4676-5_12
Reference21 articles.
1. Sheng, S., Magnien, B., Kumaraguru, P., Acquisti, A., Cranor, L. F., Hong, J., Nunge, E.: Anti-phishing Phil: the design and evaluation of a game that teaches people not to fall for phish. In: Proceedings of the 3rd Symposium on Usable Privacy and Security, pp. 88–99. ACM, Pittsburgh, Pennsylvania, USA (2007)
2. Published in Global Digital Report 2019. https://datareportal.com/. Last accessed 2020/02/21
3. Cao, Y., Han, W., Le, Y.: Anti-phishing based on automated individual white-list. In: Proceedings of the 4th ACM workshop on Digital identity management, pp. 51–6 0. ACM (2008)
4. Aksu, D., Turgut, Z., Üstebay, S., Aydin, M.A.: Phishing analysis of websites using classification techniques. In: International Telecommunications Conference, pp. 251–258. Springer, Singapore (2019)
5. Lam, T., Kettani, H.: PhAttApp: A phishing attack detection application. In: Proceedings of the 2019 3rd International Conference on Information System and Data Mining, pp. 154–158. Houston, TX, USA (2019)
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