Abstract
Internet-based sources facing security problem because of the most sophisticated phishing attacks on online world. Advanced persistent threat attackers are using targeted emails, phishing websites and social engineering techniques to reach their goals. Deceptive Phishing targets confidential information using social engineering thefts online identity and uses spoofed emails and lure to be forged websites. In this paper we discussed about different classification and filtering methods to protect the cloud. An experimental approach is provided with implementation procedures using machine learning techniques to combat on malicious websites and email spams. We concentrated on different approaches, algorithms, techniques to detect the phishing attacks, and a new model is designed and implemented on the dataset and results are evaluated. The evaluation metrics are implemented on datasets based on different algorithms, and results are tabulated and graphical analysis is done.
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Chandra, J.V., Challa, N., Pasupuleti, S.K. (2020). Detection of Deceptive Phishing Based on Machine Learning Techniques. In: Fiaidhi, J., Bhattacharyya, D., Rao, N. (eds) Smart Technologies in Data Science and Communication. Lecture Notes in Networks and Systems, vol 105. Springer, Singapore. https://doi.org/10.1007/978-981-15-2407-3_2
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DOI: https://doi.org/10.1007/978-981-15-2407-3_2
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