Title | Web Phishing Detection using Neural Network Framework |
Publication Type | Journal Article |
Year of Publication | 2020 |
Authors | Naksha, V., S. G. Shaila, and A. Vadivel |
Journal | International Journal of Creative Research Thoughts (IJCRT) |
Volume | 8 |
Pagination | 3060-3065 |
Date Published | 2020 |
Type of Article | Article |
ISBN Number | 2320-2882 (ISSN) |
Keywords | Computer Science and Engineering, Others |
Abstract | In recent times, Phishing poses a major threat to individuals in regular day to day activities. Phishers use mock email and send illicit links to obtain solitary data and money related records, for example, usernames and passwords. Through veiling unlawful URLs aslegitimate ones, aggressors can deceive clients to visit the phishing URLs to get private data and other private information’s. Identification of Phishing websites and reliable websites costs many Internet handlers millions of dollars. The frameworks as on today foridentifying phishing websites are on a very basic level and new techniques are expected to take big leap in identifying the dangers presented by phishing assaults. One of those techniques involves the usage of Index Value to assess the effect of ideal highlights onphishing websites. These ideal highlights are utilized to build the neural system and an ideal classifier is made to detect the phishing sites. The technique presented here can exclude the over-fitting issue of the neural system to a greater degree. |
URL | https://ijcrt.org/papers/IJCRT2007299.pdf |
Short Title | IJCRT |