Author:
Dzeha Eric Edem,Jourdan Guy-Vincent
Publisher
Springer Nature Switzerland
Reference42 articles.
1. Aggarwal, A., Rajadesingan, A., Kumaraguru, P.: Phishari: automatic realtime phishing detection on twitter. In: 2012 eCrime Researchers Summit, pp. 1–12 (2012). https://doi.org/10.1109/eCrime.2012.6489521
2. Alom, Z., Carminati, B., Ferrari, E.: A deep learning model for twitter spam detection. Online Soc. Netw. Media 18, 100079 (2020). https://doi.org/10.1016/j.osnem.2020.100079
3. Azeez, N.A., Misra, S., Margaret, I.A., Fernandez-Sanz, L., et al.: Adopting automated whitelist approach for detecting phishing attacks. Comput. Sec. 108, 102328 (2021)
4. Bell, S., Paterson, K., Cavallaro, L.: Catch me (on time) if you can: understanding the effectiveness of twitter url blacklists. arXiv preprint arXiv:1912.02520 (2019)
5. Bouijij, H., Berqia, A.: Machine learning algorithms evaluation for phishing urls classification. In: 2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT), pp. 01–05 (2021). https://doi.org/10.1109/ISAECT53699.2021.9668489