Automatic Smishing Detection System with Feedback Loops

This is the authors' abstract. We don't add key points for this paper.

Abstract This study delves into the escalating issue of Smishing, an emerging menace within the information security landscape spurred by the widespread use of text messages on smartphones. Smishing, a portmanteau of SMS and Phishing, involves attackers disseminating SMS with malicious content to unsuspecting victims. This content often harbors links that redirect users to websites housing malicious applications and deceptive user interfaces. The primary goal of this study is to construct an artificial intelligence-based Anti-Smishing filter capable of detecting and thwarting Smishing attempts. The societal significance of this research is underscored by the imperative to safeguard personal information in the face of a continuously evolving threat landscape. The detrimental impact of Smishing on individual security, encompassing both financial and personal realms, underscores the necessity for innovative solutions. Addressing this issue necessitates the development of a machine learning model specifically tailored to identify the distinct characteristics of Smishing. While the final results are pending, the strides made thus far indicate a substantial contribution toward the establishment of an effective filter. This research project is poised to yield tangible solutions to counteract Smishing, thereby fortifying the security of personal information in the global context of mobile communications. By creating a robust defense mechanism against Smishing attempts, this initiative aligns with the broader objective of enhancing cybersecurity and preserving the integrity of personal data in an increasingly interconnected and vulnerable digital environment.