Phishing Detection in IMs using Domain Ontology and CBA - An innovative Rule Generation Approach

TL;DR

This paper presents a novel, context-aware approach for detecting phishing in instant messaging by combining domain ontology with classification-based rule generation, significantly improving detection accuracy.

Contribution

It introduces a dynamic, intelligent phishing detection framework for IMs using domain ontology and CBA for rule creation, addressing a gap in existing research.

Findings

Enhanced precision and recall over existing methods

Effective detection of phishing in instant messages

Improved user safety and trust in IM platforms

Abstract

User ignorance towards the use of communication services like Instant Messengers, emails, websites, social networks etc. is becoming the biggest advantage for phishers. It is required to create technical awareness in users by educating them to create a phishing detection application which would generate phishing alerts for the user so that phishing messages are not ignored. The lack of basic security features to detect and prevent phishing has had a profound effect on the IM clients, as they lose their faith in e-banking and e-commerce transactions, which will have a disastrous impact on the corporate and banking sectors and businesses which rely heavily on the internet. Very little research contributions were available in for phishing detection in Instant messengers. A context based, dynamic and intelligent phishing detection methodology in IMs is proposed, to analyze and detect phishing in Instant Messages with relevance to domain ontology (OBIE) and utilizes the Classification based on Association (CBA) for generating phishing rules and alerting the victims. A PDS Monitoring system algorithm is used to identify the phishing activity during exchange of messages in IMs, with high ratio of precision and recall. The results have shown improvement by the increased percentage of precision and recall when compared to the existing methods.