SMS Fraud Detection Using Machine Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-0901-6_52
Reference14 articles.
1. El-Alfy ESM, AlHasan AA (2016) Spam filtering framework for multimodal mobile communication based on dendritic cell algorithm. Future Gen Comput Syst 64:98–107. https://doi.org/10.1016/j.future.2016.02.018
2. Jialin M, Zhang Y, Liu J, Yu K, Wang X (2016) Intelligent SMS spam filtering using topic model. In: International conference on intelligent networking and collaborative systems (INCoS), pp 380–383. IEEE. https://doi.org/10.1109/INCoS.2016.47
3. Chan PPK, Yang C, Yeung DS, Ng WWY (2015) Spam filtering for short messages in adversarial environment. Neurocomputing 155:167–176. https://doi.org/10.1016/j.neucom.2014.12.034
4. Delany SJ, Buckley M, Greene D (2012) SMS spam filtering: methods and data. Expert Syst Appl 39:9899–9908. https://doi.org/10.1016/j.eswa.2012.02.053
5. Xu Q, Xiang EW, Yang Q, Du J, Zhong J (2012) SMS spam detection using non-content features. IEEE Intell Syst 27(6):44–51
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