Hierarchical Classification Model for SMS: An Evolving Model for HAM Categorization

With the exponential growth of Short Message Service (SMS) usage, a pressing challenge has emerged: the proliferation of unwanted spam messages that disrupt user experience and jeopardize data privacy. Ham refers to legitimate and desired messages, whereas spam pertains to unwanted and unsolicited messages. However, the proliferation of spam SMS messages has escalated to the point of constituting critical cyber threats. Moreover, the sheer volume of messages has become an increasing inconvenience. In response, our study present the Spam-HamCategorization(SPHAM-CAT model), a solution that adeptly distinguishes between “spam” and “ham” messages, leveraging established text classification methods. This innovative approach focuses on analyzing linguistic features, idiomatic expressions, and content patterns to significantly enhance spam detection precision. By addressing both the security and user experience aspects, the SPHAM-CAT model introduces a paradigm shift in SMS communication management.