An Awareness About Phishing Attack And Fake News Using Machine Learning Technique

Abstract

In this decade Social Media platforms and online websites plays an important role in bringing people together, gathering information and easy way for transferring the information. Social media news consumption provides both positive and negative impacts to this world. News is spreading rapidly using social media. On the other hand, it facilitates the spread of fake news. Wrong, and untruthful information. The phishing is one of the serious cyber threats to people's everyday lives and the internet environment in these attacks, the attacker impersonates a trusted entity with the intent of stealing sensitive information or the user's digital identity, such as account information, credit card and debit card numbers, CVV, pin and other user details. Therefore, Phishing website and fake news detection is an important need in our society. In this project phishing website detection is proposed using Logistic Regression and Naïve Bayes machine learning algorithms. Tf-idfVectorizer, CountVectorizer, Logistic Regression, Decision Tree Classifier and Random Forest Classifier are used for detecting the fake news.