Comparison of Ensemble Simple Feedforward Neural Network and Deep Learning Neural Network on Phishing Detection-Reference-Cited by-同舟云学术

Comparison of Ensemble Simple Feedforward Neural Network and Deep Learning Neural Network on Phishing Detection

Published:2020 Issue: Volume: Page:595-604
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Soon Gan Kim,Chiang Liew Chean,On Chin Kim,Rusli Nordaliela Mohd,Fun Tan Soo

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-0058-9_57

Reference23 articles.

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2. Gupta, B. B., Tewari, A., Jain, A. K., Agrawal, D. P.: Fighting against phishing attacks: state of the art and future challenges. Neural Computing and Applications 28(12), 3629-3654 (2017).

3. Gupta, B. B., Arachchilage, N. A., Psannis, K. E.: Defending against phishing attacks: taxonomy of methods, current issues and future directions. Telecommunication Systems 67(2), 247-267 (2018).

4. Chin, K. O., Chang, K. T., Teo, J., Alfred, R., Cheng, W., Tan, T. G.: Self-Evaluation of RTS Troop’s Performance. Journal Teknologi. UTM Press. 76(12), 119–126 (2015).

5. Tan, T. G., Yong, Y. N., Chin, K. O., Teo, J., Alfred, R.: Automated Evaluation for AI Controllers in Tower Defense Game Using Genetic Algorithm. CCIS 378, Springer-Verlag Berlin Heidelberg, 135–146 (2013).

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