A ROBUST METHOD FOR EFFICIENT SPAM DETECTION

Abstract: In this day and age of popular instant messaging programmes, Short Message Service (SMS) has lost importance and has become the domain of service providers, commercial houses, and various organisations that utilise this service to target common consumers for marketing and spamming. Acurrent trend in spam messaging is the use of content in regional language written in English, which makes identification and filtering of such communications more difficult. In this paper, an expanded version of a typical SMS corpus including spam and non-spam texts is used, which is enhanced by the addition of labelled messages. According to local cell phone users, text messages in regional languages like Hindi or Bengali written in English have been utilised. The Monte Carlo method is utilized for learning and categorization in Using a collection of characteristics and machine learning strategies that are regularly employed by researchers. The findings show how different algorithms perform in effectively tackling the given task.

Keywords: Network security, data storage, privacy key, Machine Learning, GCR-MN, CNN