SpamFender: A Semi-supervised Incremental Spam Classification System across Social Networks

Shengyuan Wen, Weiqing Sun

2022

Abstract

Social network users receive a large amount of social data every day. These data may contain malicious unwanted social spams, even though each social network has its social spam filtering mechanism. Moreover, spammers may send spam to multiple social networks concurrently, and the spam on the same topic from different social networks has similarities. Therefore, it is crucial to building a universal spam detection system across different social networks that can effectively fend off spam continuously. In this paper, we designed and implemented a tool Spam-Fender to facilitate spam detection across social networks. In order to utilize the raw social data obtained from multiple social networks, we utilized a semi-supervised learning method to convert unlabelled data into usable data for training the model. Moreover, we developed an incremental learning method to enable the model to learn new data continuously. Performance evaluations demonstrate that our proposed system can effectively detect social spam with satisfactory accuracy levels. In addition, we conducted a case study on the COVID-19 dataset to evaluate our system.

Paper Citation

in Harvard Style

Wen S. and Sun W. (2022). SpamFender: A Semi-supervised Incremental Spam Classification System across Social Networks. In Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-553-1, pages 388-395. DOI: 10.5220/0010840300003120

in Bibtex Style

@conference{icissp22,
author={Shengyuan Wen and Weiqing Sun},
title={SpamFender: A Semi-supervised Incremental Spam Classification System across Social Networks},
booktitle={Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2022},
pages={388-395},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010840300003120},
isbn={978-989-758-553-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - SpamFender: A Semi-supervised Incremental Spam Classification System across Social Networks
SN - 978-989-758-553-1
AU - Wen S.
AU - Sun W.
PY - 2022
SP - 388
EP - 395
DO - 10.5220/0010840300003120