<?xml version="1.0" encoding="UTF-8"?>
<doi_batch version="4.3.0" xmlns="http://www.crossref.org/doi_resources_schema/4.3.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.crossref.org/doi_resources_schema/4.3.0 http://www.crossref.org/schema/deposit/doi_resources4.3.0.xsd">
<head>
<doi_batch_id>2e644cf5-45e3-4e61-9fd0-ce3b4d944753</doi_batch_id>
<depositor>
<name>beie</name>
<email_address>director@blueeyesintelligence.org</email_address>
</depositor>
</head>
<body>
<doi_citations>
<doi>10.35940/ijrte.B8120.13020724</doi>
<citation_list><citation key="ref0"><doi>10.26438/ijcse/v9i7.2225</doi><unstructured_citation>&quot;Spammer Detection and Fake User Identification in E-Commerce Site,&quot; vol. 9, no. 7, pp. 22-25, 2021. https://doi.org/10.26438/ijcse/v9i7.2225</unstructured_citation></citation><citation key="ref1"><unstructured_citation>P. Priyadevi and V. Lalithadevi, &quot;An Efficient and Usable Client-Side Phishing Detection Application,&quot; no. 2, 2018.</unstructured_citation></citation><citation key="ref2"><doi>10.1109/LCOMM.2021.3055064</doi><unstructured_citation>C. Natalino, A. Udalcovs, L. Wosinska, O. Ozolins, and M. Furdek, &quot;Spectrum Anomaly Detection for Optical Network Monitoring Using Deep Unsupervised Learning,&quot; IEEE Commun. Lett., vol. 25, no. 5, pp. 1583-1586, 2021, doi: 10.1109/LCOMM.2021.3055064. https://doi.org/10.1109/LCOMM.2021.3055064</unstructured_citation></citation><citation key="ref3"><unstructured_citation>V. R. Reddy, C. V. M. Reddy, and M. Ebenezar, &quot;A Study on Anti-Phishing Techniques,&quot; no. 1, pp. 30-36, 2016.</unstructured_citation></citation><citation key="ref4"><unstructured_citation>H. K. N. G, G. Pooventhiran, and K. R. D, &quot;Landslide Type Prediction using Random Forest Classifier,&quot; no. 2, pp. 7-11, 2020.</unstructured_citation></citation><citation key="ref5"><doi>10.26438/ijcse/v7i5.10261031</doi><unstructured_citation>S. Khatana and A. Jain, &quot;Malware Detection Using the Behavioral Analysis of the Web-based Applications and User,&quot; Int. J. Comput. Sci. Eng., vol. 7, no. 5, pp. 1026-1031, 2019, doi: 10.26438/ijcse/v7i5.10261031. https://doi.org/10.26438/ijcse/v7i5.10261031</unstructured_citation></citation><citation key="ref6"><doi>10.26438/ijcse/v7i10.2736</doi><unstructured_citation>S. Bansal and A. Singh, &quot;Machine learning in the prediction, determination and further study of different cyber-attacks,&quot; no. 10, 2019. https://doi.org/10.26438/ijcse/v7i10.2736</unstructured_citation></citation><citation key="ref7"><doi>10.26438/ijcse/v6i2.111</doi><unstructured_citation>P. Re-identification, H. Xie, Y. Zhou, and Q. Liu, &quot;Deep Learning Feature Representation Applied to Cross Dataset,&quot; no. 2, pp. 1-11, 2018. https://doi.org/10.26438/ijcse/v6i2.111</unstructured_citation></citation><citation key="ref8"><doi>10.26438/ijcse/v7i7.4045</doi><unstructured_citation>R. V Kotawadekar, A. S. Kamble, and S. A. Surve, &quot;Automatic Detection of Fake Profiles in Online Social Networks,&quot; no. 7, 2019. https://doi.org/10.26438/ijcse/v7i7.4045</unstructured_citation></citation><citation key="ref9"><doi>10.26438/ijcse/v9i6.1318</doi><unstructured_citation>R. R. Biradar and G. S. Nagaraja, &quot;Anomalous Traffic Detection System for Enterprise using Elastic Stack with Machine Learning,&quot; vol. 9, no. 6, 2021. https://doi.org/10.26438/ijcse/v9i6.1318</unstructured_citation></citation><citation key="ref10"><doi>10.22214/ijraset.2019.4209</doi><unstructured_citation>A. Kulkarni, &quot;Credit Card Fraud Detection Using Random Forest and Local Outlier Factor,&quot; Int. J. Res. Appl. Sci. Eng. Technol., vol. 7, no. 4, pp. 1170-1175, 2019, doi: 10.22214/ijraset.2019.4209. https://doi.org/10.22214/ijraset.2019.4209</unstructured_citation></citation><citation key="ref11"><doi>10.26438/ijcse/v6i5.750755</doi><unstructured_citation>P. Raj and M. Mittal, &quot;Detection of Phishing URLs using Bayes Net and Naïve Bayes and evaluating the risk assessment using Attributable Risk,&quot; no. 5, 2018. https://doi.org/10.26438/ijcse/v6i5.750755</unstructured_citation></citation><citation key="ref12"><doi>10.26438/ijcse/v6i6.188191</doi><unstructured_citation>P. Saklecha and J. Raikwar, &quot;Prevention of Phishing Attack using Hybrid Blacklist Recommendation Algorithm,&quot; no. 6, pp. 188-191, 2018. https://doi.org/10.26438/ijcse/v6i6.188191</unstructured_citation></citation><citation key="ref13"><doi>10.26438/ijcse/v9i7.5359</doi><unstructured_citation>N. S. Reddy and V. K. M, &quot;Review Paper Detection of E-Banking Phishing Websites,&quot; no. 14, pp. 49-52, 2019. https://doi.org/10.26438/ijcse/v9i7.5359</unstructured_citation></citation><citation key="ref14"><doi>10.35940/ijitee.H6540.069820</doi><unstructured_citation>H. Agrawal and R. R. Singh, &quot;An Ensemble Approach for Detecting Phishing Attacks,&quot; vol. 9, no. 7, 2021. https://doi.org/10.35940/ijitee.H6540.069820</unstructured_citation></citation><citation key="ref15"><doi>10.35940/ijitee.H6540.069820</doi><unstructured_citation>Mabuni, D. (2020). A Novel Impurity Measuring Technique for Decision Tree Learning in Machine Learning. In International Journal of Innovative Technology and Exploring Engineering (Vol. 9, Issue 8, pp. 506-512). https://doi.org/10.35940/ijitee.h6540.069820</unstructured_citation></citation><citation key="ref16"><doi>10.35940/ijrte.F8136.038620</doi><unstructured_citation>Panhalkar, A. R., &amp; Doye, D. D. (2020). Improving Decision Tree Forest using Preprocessed Data. In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 8, Issue 6, pp. 4457-4460). https://doi.org/10.35940/ijrte.f8136.038620</unstructured_citation></citation><citation key="ref17"><doi>10.54105/ijainn.B1019.041221</doi><unstructured_citation>Assegie, T. A. (2021). K-Nearest Neighbor Based URL Identification Model for Phishing Attack Detection. In Indian Journal of Artificial Intelligence and Neural Networking (Vol. 1, Issue 2, pp. 18-21). https://doi.org/10.54105/ijainn.b1019.041221</unstructured_citation></citation><citation key="ref18"><doi>10.54105/ijdm.A1642.04010524</doi><unstructured_citation>Joshma K J, &amp; Sankar P, V. (2024). Phishing Website Detection. In Indian Journal of Data Mining (Vol. 4, Issue 1, pp. 38-41). https://doi.org/10.54105/ijdm.a1642.04010524</unstructured_citation></citation><citation key="ref19"><doi>10.35940/ijeat.F1119.0986S319</doi><unstructured_citation>Dawood, M., Ibrahim, O. B., &amp; Abu-Ulbeh, W. A. R. A. (2019). Enrich Awareness of Users to Detect Phishing Websites. In International Journal of Engineering and Advanced Technology (Vol. 8, Issue 6s3, pp. 648-650). https://doi.org/10.35940/ijeat.f1119.0986s319</unstructured_citation></citation></citation_list>
</doi_citations>
</body>
</doi_batch>
