A Survey on Secure Message—A Proposition using Machine Learning for Handling Fraudulent Messages

The spread of digital communication exposes oneself to running across malicious messages that overpower security features. This paper introduces Secure-Message, a newfangled app aimed at checking the security of messages that may arrive from any app. The Machine Learning (ML) algorithms such as Decision Tree Algorithm, Support Vector Machine or Random Forest are used to analyse the received messages and provide the user a quick, animated output to let them know if it is safe enough to open the message or not. Secure- Message functions by using advanced ML algorithms trained on a varying dataset of messages that are labelled either safe or malicious. The app will evaluate several features that include text patterns, embedded links, and Metadata in assessing the probability of the message being malicious. The ease of use is built such that this application provides a transparent interface for integration with different messaging systems. In being so easy to assess online basically, it is hoped that Secure-Message alongside the rapid communications will improve security and decrease people fall victim to phishing, malware, and other forms of cyber-attacks. This Machine Learning approach enables prompt response, thus reducing the risk through fraudulent cyber messaging and providing the needful direction. This application is easily adaptable and scalable thus providing an effective solution for the present-day cyber security challenges.