This article focuses on the design of biogeography based optimization with deep learning for Phishing Email detection and classification (BBODL-PEDC) model.
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This article focuses on the design of biogeography based optimization with deep learning for Phishing Email detection and classification (BBODL-PEDC) model. The ...
Optimal Deep Belief Network Enabled Cybersecurity Phishing Email Classification. Authors. Dutta, Ashit Kumar; Meyyappan, T.; Qureshi, Basit; Alsanea, Majed ...
Optimal Deep Belief Network Enabled Cybersecurity Phishing Email Classification ... Authors: Ashit Kumar Dutta; T. Meyyappan; Basit Qureshi; Majed Alsanea; Anas ...
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Why is it important for you to watch out for phishing emails even if your organization has email controls and security in place?
Optimal Deep Belief Network Enabled Cybersecurity Phishing Email Classification ... Network: A Conversion from Spam Email Classification to Graph Classification.
Aug 25, 2024 · This study's goal is to establish an automated system for the early detection and prevention of phishing websites, thereby enhancing online security.
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Our focus in this paper is to build an intelligent classifier at the email level that is capable of detecting phishing emails as an early stage in the phishing ...
M.M.; Sait, A.R.W. Optimal Deep Belief. Network Enabled Cybersecurity Phishing. Email Classification. Comput. Syst. Sci. Eng. 2023, 44, 2701–2713. [Google.
The proposed approach involves four steps, namely preprocessing, feature extraction, feature selection and classification, for dealing with phishing e-mails.
This work introduces the Optimized Email Classification Network (OEC single bond Net) to categorize emails and mitigate security risks effectively.
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