Show simple item record

AuthorGuangjun, Luo
AuthorNazir, Shah
AuthorKhan, Habib Ullah
AuthorHaq, Amin Ul
Available date2022-12-29T06:16:06Z
Publication Date2020-07-09
Publication NameSecurity and Communication Networks
Identifierhttp://dx.doi.org/10.1155/2020/8873639
CitationGuangJun, L., Nazir, S., Khan, H. U., & Haq, A. U. (2020). Spam detection approach for secure mobile message communication using machine learning algorithms. Security and Communication Networks, 2020.
ISSN1939-0114
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85089149424&origin=inward
URIhttp://hdl.handle.net/10576/37774
AbstractThe spam detection is a big issue in mobile message communication due to which mobile message communication is insecure. In order to tackle this problem, an accurate and precise method is needed to detect the spam in mobile message communication. We proposed the applications of the machine learning-based spam detection method for accurate detection. In this technique, machine learning classifiers such as Logistic regression (LR), K-nearest neighbor (K-NN), and decision tree (DT) are used for classification of ham and spam messages in mobile device communication. The SMS spam collection data set is used for testing the method. The dataset is split into two categories for training and testing the research. The results of the experiments demonstrated that the classification performance of LR is high as compared with K-NN and DT, and the LR achieved a high accuracy of 99%. Additionally, the proposed method performance is good as compared with the existing state-of-the-art methods.
SponsorMinistry of Education of the People's Republic of China [DCA190332].
Languageen
PublisherHindawi
SubjectSpam detection
Classification performance
Machine learning
TitleSpam Detection Approach for Secure Mobile Message Communication Using Machine Learning Algorithms
TypeArticle
Volume Number2020
ESSN1939-0122
dc.accessType Open Access


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record