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Phishing and Spam Detection: based on URL Heuristics and Email Text Analysis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 14 |
| Year of Publication: 2025 |
| Authors: Aditya Dusane, Sanket Dhonde, Aayush Dumbre, Omkar Indore, Rizwana Shaikh |
10.5120/ijca2025925157
|
Aditya Dusane, Sanket Dhonde, Aayush Dumbre, Omkar Indore, Rizwana Shaikh . Phishing and Spam Detection: based on URL Heuristics and Email Text Analysis. International Journal of Computer Applications. 187, 14 ( Jun 2025), 48-52. DOI=10.5120/ijca2025925157
Abstract
Phishing attacks continue to compromise cybersecurity by exploiting deceptive URLs and fraudulent emails to extract confidential user information. Traditional systems relying on static heuristics and blacklists are challenged by novel phishing tactics—especially the use of dynamically generated session URLs and subtle email cues. In this paper, we propose a dual-model approach that integrates URL-based heuristics with email text analysis using machine learning (ML) and deep learning (DL) techniques. The system extracts lexical and host-based features from URLs and leverages natural language processing (NLP) to analyze email messages. Experiments on an 11,054-sample phishing URL dataset and a 5,572-sample email dataset reveal that our method achieves a URL classification accuracy of 96.8% and an email spam detection accuracy of 99.2%, with a combined system accuracy of 98.5%. These results demonstrate the robustness of the integrated approach in addressing challenges such as flagging new links and handling dynamic URL patterns.
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