SM‐Detector: A security model based on BERT to detect SMiShing messages in mobile environments

A Ghourabi - Concurrency and Computation: Practice and …, 2021 - Wiley Online Library
The growing use of SMS by businesses to communicate with their customers has made
attackers more interested in smishing attacks. Smishing is a security attack that involves …

Spam filtering of mobile SMS using CNN–LSTM based deep learning model

SMM Hossain, JA Sumon, A Sen, MI Alam… - … Conference on Hybrid …, 2021 - Springer
In our civilizations, SMS continues to be an arguable communication tool despite the rattling
development of protocol–predicated messaging approaches. Some businesses consider …

Stratified hyperparameters optimization of feed-forward neural network for social network spam detection (SON2S)

E Elakkiya, S Selvakumar - Soft Computing, 2022 - Springer
Over the last decade, popularity and fascination for social networks have exponentially
increased. This rapid growth has triggered cybercriminals to utilize social networks for their …

Filtering turkish spam using LSTM from deep learning techniques

EE Eryılmaz, DÖ Şahin, E Kılıç - 2020 8th International …, 2020 - ieeexplore.ieee.org
E-mails are used effectively by people or communities who want to do propaganda,
advertisement, and phishing because of their ease of use and low cost. People or …

A comparative analysis of recurrent neural network and support vector machine for binary classification of spam short message service

D Odera, G Odiaga - World Journal of Advanced Engineering …, 2023 - mail.wjaets.com
Over the years, communication through Short Message Service (SMS) has been a primary
tool for mobile subscribers. SMS has varied applications in health, industry, finances …

Multi-type feature extraction and early fusion framework for SMS spam detection

HA Al-Kabbi, MR Feizi-Derakhshi… - IEEE Access, 2023 - ieeexplore.ieee.org
SMS spam is a pervasive issue that affects millions worldwide, leading to significant
inconvenience, time wastage, and potential financial scams. Given the prevalence and …

A comparative study of word embedding techniques for sms spam detection

P Joseph, SY Yerima - 2022 14th International Conference on …, 2022 - ieeexplore.ieee.org
E-mail and SMS are the most popular communication tools used by businesses,
organizations and educational institutions. Every day, people receive hundreds of messages …

Establishing an optimal online phishing detection method: Evaluating topological NLP transformers on text message data

H Milner, M Baron - Journal of Data Science and …, 2024 - researchoutput.csu.edu.au
This research establishes an optimal classification model for online SMSspamdetection by
utilizing topological sentence transformer methodologies. The study is a responsetothe …

Category-learning attention mechanism for short text filtering

T Xia, X Chen - Neurocomputing, 2022 - Elsevier
In machine translation, the attention mechanism highlights relevant words according to the
distances between the source and target vectors dynamically. However, its ability to optimize …

Email threat detection using distinct neural network approaches

E Castillo, S Dhaduvai, P Liu, KS Thakur… - Proceedings for the …, 2020 - aclanthology.org
This paper describes different approaches to detect malicious content in email interactions
through a combination of machine learning and natural language processing tools …