• Neetu Gupta
• Sonal Arora

The intense growth of smart mobile phones has contributed to the growth of online or offline Instant Messaging and SMS usage as an alternative way of Transaction and communication. The rapid growth of users, along with the faith they instinctively have in their devices, makes this kind of messages a congenial environment for spammers. In fact, reports distinctly shows that volume of spam over Instant Messaging and SMS is rapidly increasing year by year. This represents a challenging problem for classical filtering methods these days. Smishing This term represents a phishing in SMS/Messages called as Smishing is a cyber-security attack, which utilizes Short Message Service (SMS) to steal personal data/credentials of mobile users. The faith level of mobile users on their smartphones has attracted attackers to perform various mobile security attacks like Smishing. In this paper, we implement the SMS-Case-based data mining classification approach to classify them subpart of SMS category by detecting of Illegitimate/Smishing messages. This proposed approach identified more than fifteen Cases which can efficiently classify them into three parts like- Primary/Useful, Illegitimate/Fraud/Smishing SMS. Furthermore, our approach applies different classification algorithms to train these renowned Cases. Since the SMS/ Messages text are usually short and generally written in Lingo language, we have used text normalization to convert them into standard form to get better Cases [1]. The performance of the proposed approach is evaluated, and it achieved more than 99% true negative rate. Further, the proposed approach is very effective for the detection of the zero hour attack too and we will classify them into three subparts, like Primary/Useful, Illegitimate/Smishing, Promotional/Others. This classification data can be used to make a better enhanced existing SMS/Message application, by providing an enhanced version of SMS application

SMS, Message Analysis, Smishing, Illegitimate, SMS Classification, Data Mining, Cases, Phishing, Short Messages,

"Case Based Architecture to Categorize SMS in Mobile System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 1, page no.1052-1057, January 2020, Available :http://www.jetir.org/papers/JETIR1908A97.pdf

"Case Based Architecture to Categorize SMS in Mobile System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 1, page no. pp1052-1057, January 2020, Available at : http://www.jetir.org/papers/JETIR1908A97.pdf