Visible to the public A Machine Learning Approach for URL Based Web Phishing Using Fuzzy Logic as Classifier

TitleA Machine Learning Approach for URL Based Web Phishing Using Fuzzy Logic as Classifier
Publication TypeConference Paper
Year of Publication2019
AuthorsChapla, Happy, Kotak, Riddhi, Joiser, Mittal
Conference Name2019 International Conference on Communication and Electronics Systems (ICCES)
PublisherIEEE
ISBN Number978-1-7281-1261-9
Keywordsclassifier, Computer crime, Conferences, credential information, data mining, Databases, feature extraction, financial information, Fuzzy logic, fuzzy logic classifier, Human Behavior, human factors, Internet, learning (artificial intelligence), machine learning, pattern classification, phishing, phishing attacks, Phishing Detection, phishing site, phishing URL, pubcrawl, security of data, Uniform resource locators, URL based Web phishing, Web mining, Web sites
Abstract

Phishing is the major problem of the internet era. In this era of internet the security of our data in web is gaining an increasing importance. Phishing is one of the most harmful ways to unknowingly access the credential information like username, password or account number from the users. Users are not aware of this type of attack and later they will also become a part of the phishing attacks. It may be the losses of financial found, personal information, reputation of brand name or trust of brand. So the detection of phishing site is necessary. In this paper we design a framework of phishing detection using URL.

URLhttps://ieeexplore.ieee.org/document/9002145
DOI10.1109/ICCES45898.2019.9002145
Citation Keychapla_machine_2019