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Identification Phishing Websites Using Machine Learning .
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The phishing process is a huge threat to society these days. These websites target human information rather than hacking into our systems. It is a process where the criminal attacks a victim online to obtain the victim’s data. Nowadays, phishing is one of the massive attacks on the users of the World Wide Web. Each time an attacker will use a new technique new way to attack a user. Hence, it is needful to have a real-time solution that is fast, reliable, and mainly efficient. Here, we develop a system that is efficient and reliable and which is adaptive to the changing environment. URLs are unique for all the websites also it is an identity of a website, so here we use the URL data as input and identify a phishing website and help the users from getting phished. This project offers an intelligent system that identifies a phishing website. The system uses the Logistic Regression technique for identification. Since the Logistic Regression technique has reportedly has good performance in classification it has been selected.
Keywords
-Phishing, Anti-Phishing, Websites, Detection, Identification, Legitimate.
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- Rishikesh Mahajan (2018) “Phishing Website Detection using Machine Learning Algorithms”
- Purvi Pujara, M. B.Chaudhari (2018) “Phishing Website Detection using Machine Learning : A Review”
- Satish.S, Suresh Babu.K (2013) “Phishing Websites Detection Based On Web Source Code And Url In The Webpage”
- Tenzin Dakpa, Peter Augustine (2017) “Study of Phishing Attacks and Preventions”
- Arun Kulkarni, Leonard L. Brown (2019) “Phishing Websites Detection using Machine Learning”
- Zuochao Dou, Issa Khalil (2017) “Systematization of Knowledge (SoK):
- A Systematic Review of Software-Based Web Phishing Detection”
- Purvi Pujara, M. B.Chaudhari (2018) “Phishing Website Detection using
- Machine Learning : A Review”
- Satish.S, Suresh Babu.K (2013) “Phishing Websites Detection Based On
- Web Source Code And Url In The Webpage”
- Guang-Gang Geng, Zhi-Wei Yan, Yu Zeng, Xiao-Bo Jin (2018) “RRPhish: Anti-Phishing via Mining Brand Resources Request”
- Srushti Patil, Sudhir Dhage (2019) “A Methodical Overview on Phishing Detection along with an OrganizedWay to Construct an AntiPhishing Framework”
- Mohammed Hazim Alkawaz, Stephanie Joanne Steven, Asif Iqbal Hajamydeen (2019) “Detecting Phishing Website Using Machine Learning” .
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