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Key insights into recommended SMS spam detection datasets [PDF]
Scientific ReportsShort Message Service (SMS) spam poses significant risks, including financial scams and phishing attempts. Although numerous datasets from online repositories have been utilized to address this issue, little attention has been given to evaluating their ...
Mohammad Firdaus Johari +6 more
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A Spam Transformer Model for SMS Spam Detection [PDF]
IEEE Access, 2021 In this paper, we aim to explore the possibility of the Transformer model in detecting the spam Short Message Service (SMS) messages by proposing a modified Transformer model that is designed for detecting SMS spam messages.
Xiaoxu Liu, Haoye Lu, Amiya Nayak
doaj +5 more sources
A Discrete Hidden Markov Model for SMS Spam Detection [PDF]
Applied Sciences, 2020 Many machine learning methods have been applied for short messaging service (SMS) spam detection, including traditional methods such as naïve Bayes (NB), vector space model (VSM), and support vector machine (SVM), and novel methods such as long short ...
Tian Xia, Xuemin Chen
doaj +4 more sources
Digital Communications and NetworksShort Message Service (SMS) is a widely used and cost-effective communication medium that has unfortunately become a frequent target for unsolicited messages - commonly known as SMS spam.
Mohammad Amaz Uddin +4 more
doaj +5 more sources
Enhancing Spam Message Classification and Detection Using Transformer-Based Embedding and Ensemble Learning [PDF]
Sensors, 2023 Over the last decade, the Short Message Service (SMS) has become a primary communication channel. Nevertheless, its popularity has also given rise to the so-called SMS spam.
Abdallah Ghourabi, Manar Alohaly
doaj +2 more sources
Cross-lingual SMS spam detection using GAN-based augmentation for imbalanced datasets [PDF]
Scientific ReportsSMS spam detection remains a critical challenge in mobile communication security, particularly when addressing the inherent class imbalance present in real-world datasets, where spam messages constitute only 13–15% of total communications.
Adnane Filali +7 more
doaj +2 more sources
A Hybrid CNN-LSTM Model for SMS Spam Detection in Arabic and English Messages
Future Internet, 2020 Despite the rapid evolution of Internet protocol-based messaging services, SMS still remains an indisputable communication service in our lives until today. For example, several businesses consider that text messages are more effective than e-mails. This
Abdallah Ghourabi +2 more
doaj +3 more sources
SMS Spam Detection using H2O Framework
Procedia Computer Science, 2017 Abstract SMS spams are one of the concerns and many people do not like to receive them since they are annoying. Many SMS spam detection methods already exist and different classifiers were used, such classifiers depended on Support Vector machine, Naive Bays and many other machine learning algorithms.
Ghazi Al-Naymat
exaly +3 more sources
EAD: effortless anomalies detection, a deep learning based approach for detecting outliers in English textual data [PDF]
PeerJ Computer ScienceAnomalies are the existential abnormalities in data, the identification of which is known as anomaly detection. The absence of timely detection of anomalies may affect the key processes of decision-making, fraud detection, and automated classification ...
Xiuzhe Wang
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IEEE AccessThe persistence of SMS spam remains a significant challenge, highlighting the need for research aimed at developing systems capable of effectively handling the evasive strategies used by spammers.
Muhammad Salman +2 more
doaj +3 more sources