Enhancing Social Media Security: An Incremental Learning-Based Spammer Detection Model

DOI

10.2991/978-94-6463-858-5_70How to use a DOI?

Keywords

Social networks; spam detection; social spammers; adaptive learning; incremental learning; machine learning; supervised learning; semi-supervised learning; Social Honeypot Dataset; classifier; detection accuracy; recall; precision

Abstract

Social networks include a large number of social members who cooperatively forward messages. However, spammers publish links to the virus and view or follow a large number of users, creating many misleading news on mobile social networks. In this article, we propose an adaptive model for social spammer detection (ASC). Create a spammer classifier with a few labeled patterns and some untruth patterns. Prediction accuracy is higher than traditional monitored learning methods. Furthermore, the time and energy required to identify social member identities is reduced by using ASD. Because social spammers frequently change their behavior and deceive spammer recognition models, incremental learning methods have been designed to allow adaptive updates to spammer recognition models. Evaluate ASDs by comparing other supervised and semi-monitoring machine methods with social honeypot datasets. Experimental results show that the proposed model exceeds the basic method in terms of recall and accuracy. Additionally, ASD maintains a high level of awareness by updating the model with newly generated social media data.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Md. Fazlunnisa
AU  - A. Sai Geethika
AU  - G. Fayaz Hussain
AU  - T. Naga Sathvika
AU  - S. Likitha
PY  - 2025
DA  - 2025/11/04
TI  - Enhancing Social Media Security: An Incremental Learning-Based Spammer Detection Model
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 830
EP  - 838
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_70
DO  - 10.2991/978-94-6463-858-5_70
ID  - Fazlunnisa2025
ER  -