Phishing Website Detection Using Neural Network and Deep Belief Network-Reference-Cited by-同舟云学术

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Phishing Website Detection Using Neural Network and Deep Belief Network

Published:2018-11-04 Issue: Volume: Page:293-300
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Verma Maneesh Kumar,Yadav Shankar,Goyal Bhoopesh Kumar,Prasad Bakshi Rohit,Agarawal Sonali

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-8639-7_30

Reference12 articles.

1. Jo, I., Jung, E., Yeom, H.Y.: You’re not who you claim to be: website identity check for phishing detection. In: 2010 Proceedings of 19th International Conference on Computer Communications and Networks, Aug 2010

2. Abunadi, A., Akanbi, O., Zainal, A.: Feature extraction process: a phishing detection approach. In: Intelligent Systems Design and Applications (ISDA), 2013 13th International Conference on, pp. 331–335. IEEE (2013)

3. Shrestha, N., Kharel, R.K., Britt, J., Hasan, R.: High-performance classification of phishing URLs using a multi-modal approach with MapReduce. In: 2015 IEEE World Congress on Services (SERVICES), pp. 206–212. IEEE (2015)

4. Prasad, B.R., Agarwal, S.: Comparative study of big data computing and storage tools: a review. Int. J. Database Theory Appl. 9(1), 45–66 (2016)

5. Li, B., Sun, R., Fang, X., Luo, X., Chang, W.: Emergent challenges and IPDS for anti-phishing attack. In: 2014 International Conference on IT Convergence and Security (ICITCS), pp. 1–4. IEEE (2014)

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