{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T12:46:28Z","timestamp":1786538788636,"version":"build-2736575974"},"reference-count":26,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,7,29]],"date-time":"2023-07-29T00:00:00Z","timestamp":1690588800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Security in the blockchain has become a topic of concern because of the recent developments in the field. One of the most common cyberattacks is the so-called phishing attack, wherein the attacker tricks the miner into adding a malicious block to the chain under genuine conditions to avoid detection and potentially destroy the entire blockchain. The current attempts at detection include the consensus protocol; however, it fails when a genuine miner tries to add a new block to the blockchain. Zero-trust policies have started making the rounds in the field as they ensure the complete detection of phishing attempts; however, they are still in the process of deployment, which may take a significant amount of time. A more accurate measure of phishing detection involves machine-learning models that use specific features to automate the entire process of classifying an attempt as either a phishing attempt or a safe attempt. This paper highlights several models that may give safe results and help eradicate blockchain phishing attempts.<\/jats:p>","DOI":"10.3390\/a16080366","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T01:48:50Z","timestamp":1690768130000},"page":"366","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Machine-Learning Techniques for Predicting Phishing Attacks in Blockchain Networks: A Comparative Study"],"prefix":"10.3390","volume":"16","author":[{"given":"Kunj","family":"Joshi","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382007, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0423-0159","authenticated-orcid":false,"given":"Chintan","family":"Bhatt","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382007, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8494-9752","authenticated-orcid":false,"given":"Kaushal","family":"Shah","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382007, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dwireph","family":"Parmar","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382007, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2829-1829","authenticated-orcid":false,"given":"Juan M.","family":"Corchado","sequence":"additional","affiliation":[{"name":"BISITE Research Group, University of Salamanca, 37007 Salamanca, Spain"},{"name":"Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain"},{"name":"Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0707-6131","authenticated-orcid":false,"given":"Alessandro","family":"Bruno","sequence":"additional","affiliation":[{"name":"Department of Business, Law, Economics and Consumer Behaviour \u201cCarlo A. Ricciardi\u201d, IULM AI Laboratory, IULM University, 20143 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7552-2394","authenticated-orcid":false,"given":"Pier Luigi","family":"Mazzeo","sequence":"additional","affiliation":[{"name":"ISASI Institute of Applied Sciences & Intelligent Systems-CNR, 73100 Lecce, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Andryukhin, A.A. (2019, January 26\u201327). Phishing attacks and preventions in blockchain based projects. Proceedings of the 2019 International Conference on Engineering Technologies and Computer Science (EnT), Moscow, Russia.","DOI":"10.1109\/EnT.2019.00008"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wen, H., Fang, J., Wu, J., and Zheng, Z. (2021, January 22\u201328). 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