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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Detection of phishing attacks using machine learning |
| Authors Name: | Akkireddy Chandramouli , K Pavankumar , G Manikanta , DN Shivaganesh reddy , G Jayakumar |
| Unique Id: | IJSDR2108013 |
| Published In: | Volume 6 Issue 8, August-2021 |
| Abstract: | The expanding use of cloud services, the expanding number of users of web applications, changes in network architecture that connects devices running mobile operating systems, and continually improving network technologies all provide new cyber security challenges. As a result, network security methods, sensors, and protection methods must change to accommodate the needs and issues of users in order to counter emerging threats. Because growing application layer cyber-attacks are recognized as top risks and the key problem for network and cyber security in Phishing is a one type of social engineering attack and has become a threat for cyber world. Phishing is a form of identity theft that occur when a malicious website impersonates a legitimate one in order to acquire sensitive information such as passwords Phishing attack employ a variety of techniques such as link manipulation, filter evasion, website forgery that mimics a legitimate website. The most common approach is to set up a spoofing web page that imitates a legitimate website. Anti-phishing working groups emphasizes that phishing attacks have grown in recent years. One of the most successful methods for detecting these malicious activates is using the concept of machine learning. This is because most of phishing attacks have some common characteristics which can be identified by machine learning methods. In which machine learning model takes input as URL and helps in detecting the website whether it is legitimate or fake website. |
| Keywords: | Machine learning, Scikit-learn, Phishing attack detection |
| Cite Article: | "Detection of phishing attacks using machine learning ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.6, Issue 8, page no.77 - 83, August-2021, Available :http://www.ijsdr.org/papers/IJSDR2108013.pdf |
| Downloads: | 000337077 |
| Publication Details: | Published Paper ID: IJSDR2108013 Registration ID:193592 Published In: Volume 6 Issue 8, August-2021 DOI (Digital Object Identifier): Page No: 77 - 83 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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