Learning Model for Phishing Website Detection

EAI Endorsed Transactions on Scalable Information Systems

A. Sinha¹  M. Mehta¹  A. Suryan¹  C. Kumar¹  R. Juneja¹ 

[1] Jaypee Institute of Information Technology, Sector 62-A, Noida, UP, India;

关键词: information systems;    phishing;    machine learning;    feature extraction;    classification;    dimensionality reduction;    security;   

DOI  :  10.4108/eai.13-7-2018.163804

来源: DOAJ

【 摘 要 】

Website portal empowered with information technology are of great importance in present scenario. With access to data allaround the world, securing our information becomes an issue of topmost priority. Over the decade there have beennumerous attacks by phishing websites and people have lost huge resources. Such malicious websites, also known asphishing website, steal information of authenticate users and carry out illegal transactions by misusing the personalinformation. Phishing website links and associated e-mails are sent to billions of users daily, thereby becoming a bigconcern for cyber security. In this paper, we address the phishing problem using machine learning approach applied on ourproposed model, which uses 30 distinct features for phishing detection. We extracted multiple features from the websitelink and applied appropriate algorithms to classify the link as legitimate or phishing links.

【 授权许可】

Unknown