SMS SPAM FILTERING

Author (s) : K.Dhanalakshmi & T.Durga Devi & Mrs.C.Prabhadevi & Mrs.A.RihanaParvinBegam

---

Abstract :
Due to huge proliferation of Short Message Service (SMS), Spammers got the interest to dig their way into it in hope to reach more targets. Spam SMS can trick mobile users to give away their confidential information which can result in severe consequences. The seriousness of this problem has raised the need to develop for an accurate Spam filtration solution. Machine learning algorithms have emerged as a great tool to classify data into labels. This description fit our case perfectly as it classifies SMS into two labels: spam or ham. This paper will tackle the SMS spam filtration solutions by introducing a hybrid system using two types of machine learning techniques: supervised & unsupervised machine learning algorithms. The new hybrid system is designed with the goal to achieve a better spam filtration accuracy and F-measures.

Keywords : Short Message Service(SMS), SMS spam filtration solutions

Conference Date : 17/09/2021

Pages : 242

Paper ID : IESMDT240