Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Multi-lingual Spam SMS detection using a hybrid deep learning technique Subject The topic of the resource deep learning; ham; machine learning; smishing; spam; Spam detection Description An account of the resource Nowadays, the incremental usage of mobile phones has made spam SMS messages a big concern. Sending malicious links through spam messages harms our mobile devices physically, and the attacker might have a chance to steal sensitive information from our devices. Various state-of-the-art research works have been proposed for SMS spam detection using feature-based, machine, and deep learning techniques. These approaches have specific limitations, such as extracting and selecting signifi-cant and quality features for efficient classification. Very few deep learning techniques are only used for classifying spam detection. Moreover, the benchmark spam datasets written in English are mostly used for evaluation. Very few papers have detected spam messages for other languages. Hence, this paper creates a multilingual SMS spam dataset and proposes a hybrid deep learning technique that combines the Convolutional Neural Network and Long Short-Term Memory (LSTM) model to classify the message dataset. The performance of this proposed hybrid model has been compared with the baseline deep learning models using accuracy, precision, recall, and F1-score metrics. 2022 IEEE. Creator An entity primarily responsible for making the resource Ramanujam E.; Shankar K.; Sharma A. Source A related resource from which the described resource is derived Proceedings - 2022 IEEE Silchar Subsection Conference, SILCON 2022 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/SILCON55242.2022.10028936" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/SILCON55242.2022.10028936</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147854946&amp;doi=10.1109%2FSILCON55242.2022.10028936&amp;partnerID=40&amp;md5=ec29cdc2d6e81114e170bd9792238392" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147854946&amp;doi=10.1109%2fSILCON55242.2022.10028936&amp;partnerID=40&amp;md5=ec29cdc2d6e81114e170bd9792238392</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166547100-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ramanujam E., National Institute of Technology Silchar, Computer Science and Engineering, Assam, India; Shankar K., National Institute of Technology Silchar, Electronics and Instrumentation Engineering, Assam, India; Sharma A., Computer Science and Engineering, Christ (Deemed to Be) University, Bangalore, India