Phishing Site Prediction Using Machine Learning Algorithm
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-8493-8_54
Reference10 articles.
1. Zahid Hasan M, Sattar A, Mahmud A, Talukder KH (2019) A multifactor authentication model to mitigate the phishing attack of e-service systems from bangladesh perspective. In: Emerging research in computing, information, communication and applications, pp 75–86
2. Islam MM, Hasan MZ, Shaon RA (2019) A novel approach for client side encryption in cloud computing. In: 2019 international conference on electrical, computer and communication engineering (ECCE), Cox’sBazar, Bangladesh, pp 1–6
3. Mohammad RM, Thabtah F, Mccluskey L (2013) Predicting phishing websites based on self-structuring neural network. Neural Comput Appl, pp 443–458
4. Mohammad RM, Thabtah F, McCluskey L (2014) Intelligent rule-based phishing websites classification. IET Inf Secur, pp 153–160
5. Shahriar H, Zulkernine M (2012) Trustworthiness testing of phishing websites: a behavior model-based approach. Future Gener Comput Syst, pp 1258–1271
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