Enhancing Security in WhatsApp: A System for Detecting Malicious and Inappropriate Content

With the increasing reliance on instant messaging applications like WhatsApp, ensuring user privacy and security has become paramount. This paper argues for the need to enhance the security of the WhatsApp messaging service. An API endpoint and Chrome extension capable of detecting profanity, malicious URLs, and inappropriate images are developed to satisfy this need. In its current stage, not only can malicious URLs circulate freely through WhatsApp without any checks, but it is also easy to send inappropriate images and texts which receiving users should be careful with. We survey existing publicly available services and APIs in the domains of profanity, malicious URLs, and inappropriate images. A novel approach that incorporates the most appropriate models for our purpose in an integrated detection system, based on simple statistical models and output from the third-party APIs, is proposed. We compile two extensive datasets of profane text and malicious URLs and employ them in testing the effectiveness of our proposed model using statistical methods. Additionally, we present a publicly available proof of concept Chrome extension that incorporates our model to provide users with an added layer of protection. Finally, we discuss potential areas for future research and suggest improvements to enhance the effectiveness of the proposed system and the cybersecurity aspect of chatting applications in general.