| Title | Phishing Detection Using Machine Learning Technique |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Rashid, Junaid, Mahmood, Toqeer, Nisar, Muhammad Wasif, Nazir, Tahira |
| Conference Name | 2020 First International Conference of Smart Systems and Emerging Technologies (SMARTTECH) |
| Keywords | Credit cards, electronic commerce, machine learning, Measurement, password, phishing, principal component analysis, privacy, pubcrawl, Standards, support vector machine, Support vector machines, threat vectors, web |
| Abstract | Today, everyone is highly dependent on the internet. Everyone performed online shopping and online activities such as online Bank, online booking, online recharge and more on internet. Phishing is a type of website threat and phishing is Illegally on the original website Information such as login id, password and information of credit card. This paper proposed an efficient machine learning based phishing detection technique. Overall, experimental results show that the proposed technique, when integrated with the Support vector machine classifier, has the best performance of accurately distinguishing 95.66% of phishing and appropriate websites using only 22.5% of the innovative functionality. The proposed technique exhibits optimistic results when benchmarking with a range of standard phishing datasets of the "University of California Irvine (UCI)" archive. Therefore, proposed technique is preferred and used for phishing detection based on machine learning. |
| DOI | 10.1109/SMART-TECH49988.2020.00026 |
| Citation Key | rashid_phishing_2020 |
Phishing Detection Using Machine Learning Technique