Adewole, Kayode Sakariyah and Anuar, Nor Badrul and Kamsin, Amirrudin and Sangaiah, Arun Kumar (2019) SMSAD: a framework for spam message and spam account detection. Multimedia Tools and Applications, 78 (4). pp. 3925-3960. ISSN 1380-7501, DOI https://doi.org/10.1007/s11042-017-5018-x.
Full text not available from this repository.Abstract
Short message communication media, such as mobile and microblogging social networks, have become attractive platforms for spammers to disseminate unsolicited contents. However, the traditional content-based methods for spam detection degraded in performance due to many factors. For instance, unlike the contents posted on social networks like Facebook and Renren, SMS and microblogging messages have limited size with the presence of many domain specific words, such as idioms and abbreviations. In addition, microblogging messages are very unstructured and noisy. These distinguished characteristics posed challenges to existing email spam detection models for effective spam identification in short message communication media. The state-of-the-art solutions for social spam accounts detection have faced different evasion tactics in the hands of intelligent spammers. In this paper, a unified framework is proposed for both spam message and spam account detection tasks. We utilized four datasets in this study, two of which are from SMS spam message domain and the remaining two from Twitter microblog. To identify a minimal number of features for spam account detection on Twitter, this paper studied bio-inspired evolutionary search method. Using evolutionary search algorithm, a compact model for spam account detection is proposed, which is incorporated in the machine learning phase of the unified framework. The results of the various experiments conducted indicate that the proposed framework is promising for detecting both spam message and spam account with a minimal number of features. © 2017, Springer Science+Business Media, LLC.
| Item Type: | Article |
|---|---|
| Funders: | University Malaya Research Grant Programme (Equitable Society) under grant RP032B-16SBS |
| Uncontrolled Keywords: | Evolutionary computation; Machine learning; Microblog; Online social network; Spam account; Spam message |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 18 May 2020 03:46 |
| Last Modified: | 18 May 2020 03:46 |
| URI: | http://eprints.um.edu.my/id/eprint/24305 |
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