Author:
Kumar Rahul,Kumar Ravi,Sahu Raja Kumar,Patra Rajkumar,Ghosh Anupam
Publisher
Springer Nature Singapore
Reference20 articles.
1. Phishing Activity Trends Report, APWG 2019 (n.d.), 4th quarter. https://docs.apwg.org/reports/apwg_trends_report_q4_2019.pdf. Accessed from 15 Dec 2021
2. Zalavadia, F., Nevrekar, A., Pachpande, P., Pandey, S., Govilkar, S.: Detecting phishing attacks using natural language processing and deep learning models. J. Appl. Sci. Comput. (JASC) 378–382 (2019)
3. Deshpande, A., Chaudhary, N., Pendamkar, O., Borde, S. (2021) : Detection of phishing websites using machine learning. Int. J. Eng. Res. Technol. (IJERT) 10, 430–433
4. Shaikh, A., Shabut, A., Hossain, A.: A literature review on phishing crime, prevention review and investigation of gaps. In: 2016 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA), pp. 9–14 (2016)
5. Mahajan, R., Siddavatam, I.: Phishing website detection using machine learning algorithms. In: Int. J. Comput. Appl. 23, 45–47 (2018)