Posted Date : 07th Mar, 2025
Peer-Reviewed Journals List: A Guide to Quality Research Publications ...
Posted Date : 07th Mar, 2025
Choosing the right journal is crucial for successful publication. Cons...
Posted Date : 27th Feb, 2025
Why Peer-Reviewed Journals Matter Quality Control: The peer revie...
Posted Date : 27th Feb, 2025
The Peer Review Process The peer review process typically follows sev...
Posted Date : 27th Feb, 2025
What Are Peer-Reviewed Journals? A peer-reviewed journal is a publica...
Developing an NLP-Based System to Detect Phishing Attempts in Real-Time
Author Name : O. R. Nanthees, S. V. Suryagandhan, K. Sudharsan, R. Loganathan
ABSTRACT Phishing attacks represent a considerable risk to digital security, targeting both individuals and organizations to illicitly obtain sensitive information via deceptive messages. Conventional methods for combating phishing often depend on blacklists, rule-based strategies, and machine learning algorithms. However, these approaches frequently struggle to adapt to the continuously evolving tactics employed by cybercriminals. This paper introduces a real-time phishing detection system that utilizes Natural Language Processing (NLP) to analyze the textual characteristics of messages, emails, and web pages for accurate identification of phishing content. By incorporating advanced NLP techniques such as word embeddings, contextual analysis, and deep learning frameworks, the proposed system aims to significantly improve detection efficacy. We assess the system’s performance using metrics such as precision, recall, and F1 score, comparing it with existing models to evaluate its effectiveness. Our results demonstrate that the NLP-based approach offers substantial improvements in the identification and mitigation of phishing attempts in real-time.