Suspicious Link Analyzer Using Artificial Intelligence

With the rapid expansion of internet usage and the increased sharing of hyperlinks through emails, messages, and social media platforms, the spread of malicious or suspicious links has become a major cybersecurity concern. These links can lead to phishing websites, malware downloads, or data theft. This paper proposes an AI-driven Suspicious Link Analyzer (SLA) system that can intelligently classify and detect suspicious or harmful URLs based on their features. The proposed model uses machine learning techniques to identify patterns in URLs and predict potential threats. This paper discusses the architecture, dataset, feature extraction, and the performance of various classification algorithms in detecting suspicious links.