Cybersecurity and Phishing Detection using AI ML
Author : Sakshi Gaikwad, Bhumika Patil, Roshani Kinge, Sakshi S Jawale, Vaidai Jambhule and Dr. Aparna Vaidyanathan
Abstract :
Phishing attacks are one of the most common and dangerous cyber threats that target internet users by stealing sensitive information such as usernames, passwords, and financial details. Traditional security mechanisms like blacklists and rule-based filters are often unable to detect newly created phishing websites. Therefore, intelligent detection techniques are required to improve cyber security.
This research proposes a machine learning based approach for detecting phishing websites by analysing various website and URL features. Different machine learning algorithms can be used to classify websites as legitimate or phishing based on patterns found in the data. The proposed system focuses on improving detection accuracy and reducing false positives by analysing multiple characteristics of websites such as URL structure, domain information, and webpage behaviour.
Experimental results demonstrate that machine learning techniques can effectively identify phishing websites and enhance user protection against cyber-attacks. The study highlights the importance of intelligent security systems in combating modern cyber threats and protecting users from online fraud.
Keywords :
Phishing Detection, Cyber Security, Machine Learning, URL Analysis, Website Classification, Network Security, Online Fraud Detection, Web Security.
