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dc.contributor.authorRao, R.S.
dc.contributor.authorPais, A.R.
dc.identifier.citationComputers and Security, 2019, Vol.83, , pp.246-267en_US
dc.description.abstractStealing of sensitive information (username, password, credit card information and social security number, etc.) using a fake webpage that imitates trusted website is termed as phishing. Recent techniques use search engine based approach to counter the phishing attacks as it achieves promising detection accuracy. But, the limitation of this approach is that it fails when phishing page is hosted on compromised server. Moreover, it also results in low true negative rate when newly registered or non-popular domains are encountered. Hence, in this paper, we propose an application named as Jail-Phish, which improves the accuracy of the search engine based techniques with an ability to detect the Phishing Sites Hosted on Compromised Servers (PSHCS) and also detection of newly registered legitimate sites. Jail-Phish compares the suspicious site and matched domain in the search results for calculating the similarity score between them. There exists some degree of similarity such as logos, favicons, images, scripts, styles, and anchorlinks within the pages of the same website whereas on the other side, the dissimilarity within the pages is very high in PSHCS. Hence, we use the similarity score between the suspicious site and matched domain as a parameter to detect the PSHCS. From the experimental results, it is observed that Jail-Phish achieved an accuracy of 98.61%, true positive rate of 97.77% and false positive rate less than 0.64%. 2019 Elsevier Ltden_US
dc.titleJail-Phish: An improved search engine based phishing detection systemen_US
Appears in Collections:1. Journal Articles

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