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We have also integrated five heuristics with the search engine-based mechanism to improve the detection accuracy, as some newly created legitimate sites may not appear in the search engine. The proposed method can also correctly classify the newly created legitimate sites that are not classified by available search engine-based methods. Evaluation results show that our method outperforms the available search-based techniques and achieves 98.15% TPR of and only 0.05% FPR.<\/jats:p>","DOI":"10.4018\/jitr.2020040106","type":"journal-article","created":{"date-parts":[[2020,2,14]],"date-time":"2020-02-14T12:09:31Z","timestamp":1581682171000},"page":"94-109","source":"Crossref","is-referenced-by-count":27,"title":["Phishing Attack Detection using a Search Engine and Heuristics-based Technique"],"prefix":"10.4018","volume":"13","author":[{"given":"Brij B.","family":"Gupta","sequence":"first","affiliation":[{"name":"National Institute of Technology, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9482-6991","authenticated-orcid":true,"given":"Ankit Kumar","family":"Jain","sequence":"additional","affiliation":[{"name":"National Institute of Technology, India"}]}],"member":"2432","reference":[{"key":"JITR.2020040106-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2017.04.006"},{"key":"JITR.2020040106-1","unstructured":"Alexa top websites. 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