Title: Cognitive information-based SMS spam detection and filtering of transliterated messages

Authors: Priyam Paul; Suheldeep Sarkar; G. Manju

Addresses: Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India ' Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India ' Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India

Abstract: SMS spam has seen an exponential increase in the past few years. This is a pain for mobile users, since any important message often gets lost in the pile of spam messages. SMS spam detection is at a very nascent stage when it comes to implementing in user devices, although there has been research in the field for a long time. We have carried out a survey of the work that has been done in the field of SMS spam filtering, and we have identified certain features which give high accuracy when classifying SMS spam pertaining to cognitive information.

Keywords: feature selection; transliteration; spam detection; spam filtering; SMS; cognitive approach; text mining.

DOI: 10.1504/IJPSPM.2024.140549

International Journal of Public Sector Performance Management, 2024 Vol.14 No.2, pp.245 - 261

Received: 20 Jul 2020
Accepted: 21 Dec 2020
Published online: 23 Aug 2024 *

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