Open Access Research Article Article ID: TCSIT-6-140

    Detection and classification of phishing websites

    Manoj P*, Bhuvan Kumar Y, Rakshitha D and Megha G

    ‘Phishing sites’ are some type of the internet security issues that mainly targets the human vulnerabilities compared to software vulnerabilities. Phishing sites are malicious websites that imitate as legitimate websites or web pages and aim to steal user’s personal credentials like user id, password, and financial information. Spotting these phishing websites is typically a challenging task because phishing is mainly a semantics-based attack, that mainly focus on human vulnerabilities, not the network or software vulnerabilities. Phishing can be elaborated as the process of charming users in order to gain their personal credentials like user-id’s and passwords. In this paper, we come up with an intelligent system that can spot the phishing sites. This intelligent system is based on a machine learning model. Our aim through this paper is to stalk a better performance classifier by examining the features of the phishing site and choose appropriate combination of systems for the training of the classifier. 


    Published on: Aug 11, 2021 Pages: 53-59

    Full Text PDF Full Text HTML DOI: 10.17352/tcsit.000040
    CrossMark Publons Harvard Library HOLLIS Search IT Semantic Scholar Get Citation Base Search Scilit OAI-PMH ResearchGate Academic Microsoft GrowKudos Universite de Paris UW Libraries SJSU King Library SJSU King Library NUS Library McGill DET KGL BIBLiOTEK JCU Discovery Universidad De Lima WorldCat VU on WorldCat


    Global Views

    Case Reports

    Peertechz Tweets

    Pinterest on TCSIT

    Help ? Google Reviews 11